Science and Understanding

A Summing Up

I started blogging in the late 1990s with a home page that I dubbed Liberty Corner (reconstructed here). I maintained the home page until 2000. When the urge to resume blogging became irresistible in 2004, I created the Blogspot version of Liberty Corner, where I blogged until May 2008.

My weariness with “serious” blogging led to the creation of Americana, Etc., “A blog about baseball, history, humor, language, literature, movies, music, nature, nostalgia, philosophy, psychology, and other (mostly) apolitical subjects.” I began that blog in July 2008 and posted there sporadically until September 2013.

But I couldn’t resist commenting on political, economic, and social issues, so I established Politics & Prosperity in February 2009. My substantive outpourings ebbed and flowed, until August 2015, when I hit a wall.

Now, almost two decades and more than 3,000 posts since my blogging debut, I am taking another rest from blogging — perhaps a permanent rest.

Instead of writing a valedictory essay, I chose what I consider to be the best of my blogging, and assigned each of my choices to one of fifteen broad topics. (Many of the selections belong under more than one heading, but I avoided repetition for the sake of brevity.) You may jump directly to any of the fifteen topics by clicking on one of these links:

Posts are listed in chronological order under each heading. If you are looking for a post on a particular subject, begin with the more recent posts and work your way backward in time, by moving up the list or using the “related posts” links that are included in most of my posts.

Your explorations may lead you to posts that no longer represent my views. This is especially the case with respect to John Stuart Mill’s “harm principle,” which figures prominently in my early dissertations on libertarianism, but which I have come to see as shallow and lacking in prescriptive power. Thus my belief that true libertarianism is traditional conservatism. (For more, see “On Liberty and Libertarianism” in the sidebar and many of the posts under “X. Libertarianism and Other Political Philosophies.”)

The following list of “bests” comprises about 700 entries, which is less than a fourth of my blogging output. I also commend to you my “Not-So-Random Thoughts” series — I, II, III, IV, V, VI, VII, VIII, IX, X, XI, XII, XIII, XIV, XV, and XVI — and “The Tenor of the Times.”

I. The Academy, Intellectuals, and the Left
Like a Fish in Water
Why So Few Free-Market Economists?
Academic Bias
Intellectuals and Capitalism
“Intellectuals and Society”: A Review
The Left’s Agenda
We, the Children of the Enlightenment
The Left and Its Delusions
The Spoiled Children of Capitalism
Politics, Sophistry, and the Academy
Subsidizing the Enemies of Liberty
The Culture War
Ruminations on the Left in America
The Euphemism Conquers All
Defending the Offensive


II. Affirmative Action, Race, and Immigration
Affirmative Action: A Modest Proposal
After the Bell Curve
A Footnote . . .
Schelling and Segregation
Illogic from the Pro-Immigration Camp
Affirmative Action: Two Views from the Academy, Revisited
Race and Reason: The Victims of Affirmative Action
Race and Reason: The Achievement Gap — Causes and Implications
Evolution and Race
“Wading” into Race, Culture, and IQ
Evolution, Culture, and “Diversity”
The Harmful Myth of Inherent Equality
Nature, Nurture, and Inequality


III. Americana, Etc.: Movies, Music, Nature, Nostalgia, Sports, and Trivia
Speaking of Modern Art
Making Sense about Classical Music
An Addendum about Classical Music
My Views on Classical Music, Vindicated
But It’s Not Music
Mister Hockey
Testing for Steroids
Explaining a Team’s W-L Record
The American League’s Greatest Hitters
The American League’s Greatest Hitters: Part II
Conducting, Baseball, and Longevity
Who Shot JFK, and Why?
The Passing of Red Brick Schoolhouses and a Way of Life
Baseball: The King of Team Sports
May the Best Team Lose
All-Time Hitter-Friendly Ballparks (With Particular Attention to Tiger Stadium)
A Trip to the Movies
Another Trip to the Movies
The Hall of Fame Reconsidered
Facts about Presidents (a reference page)


IV. The Constitution and the Rule of Law
Unintended Irony from a Few Framers
Social Security Is Unconstitutional
What Is the Living Constitution?
The Legality of Teaching Intelligent Design
The Legality of Teaching Intelligent Design: Part II
Law, Liberty, and Abortion
An Answer to Judicial Supremacy?
Final (?) Words about Preemption and the Constitution
More Final (?) Words about Preemption and the Constitution
Who Are the Parties to the Constitutional Contract?
The Slippery Slope of Constitutional Revisionism
The Ruinous Despotism of Democracy
How to Think about Secession
A New, New Constitution
Secession Redux
A Declaration of Independence
First Principles
The Constitution: Original Meaning, Corruption, and Restoration
The Unconstitutionality of the Individual Mandate
Does the Power to Tax Give Congress Unlimited Power?
Does Congress Have the Power to Regulate Inactivity?
Substantive Due Process and the Limits of Privacy
The Southern Secession Reconsidered
Abortion and the Fourteenth Amendment
Obamacare: Neither Necessary nor Proper
Privacy Is Not Sacred
Our Perfect, Perfect Constitution
Reclaiming Liberty throughout the Land
Obamacare, Slopes, Ratchets, and the Death-Spiral of Liberty
Another Thought or Two about the Obamacare Decision
Secession for All Seasons
Restoring Constitutional Government: The Way Ahead
“We the People” and Big Government
How Libertarians Ought to Think about the Constitution
Abortion Rights and Gun Rights
The States and the Constitution
Getting “Equal Protection” Right
How to Protect Property Rights and Freedom of Association and Expression
The Principles of Actionable Harm
Judicial Supremacy: Judicial Tyranny
Does the Power to Tax Give Congress Unlimited Power? (II)
The Beginning of the End of Liberty in America
Substantive Due Process, Liberty of Contract, and States’ “Police Power”
U.S. Supreme Court: Lines of Succession (a reference page)


V. Economics: Principles and Issues
Economics: A Survey (a reference page that gives an organized tour of relevant posts, many of which are also listed below)
Fear of the Free Market — Part I
Fear of the Free Market — Part II
Fear of the Free Market — Part III
Trade Deficit Hysteria
Why We Deserve What We Earn
Who Decides Who’s Deserving?
The Main Causes of Prosperity
That Mythical, Magical Social Security Trust Fund
Social Security, Myth and Reality
Nonsense and Sense about Social Security
More about Social Security
Social Security Privatization and the Stock Market
Oh, That Mythical Trust Fund!
The Real Meaning of the National Debt
Socialist Calculation and the Turing Test
Social Security: The Permanent Solution
The Social Welfare Function
Libertarian Paternalism
A Libertarian Paternalist’s Dream World
Talk Is Cheap
Giving Back to the Community
The Short Answer to Libertarian Paternalism
Second-Guessing, Paternalism, Parentalism, and Choice
Another Thought about Libertarian Paternalism
Why Government Spending Is Inherently Inflationary
Ten Commandments of Economics
More Commandments of Economics
Capitalism, Liberty, and Christianity
Risk and Regulation
Back-Door Paternalism
Liberty, General Welfare, and the State
Another Voice Against the New Paternalism
Monopoly and the General Welfare
The Causes of Economic Growth
Slippery Paternalists
The Importance of Deficits
It’s the Spending, Stupid!
There’s More to Income than Money
Science, Axioms, and Economics
Mathematical Economics
The Last(?) Word about Income Inequality
Why “Net Neutrality” Is a Bad Idea
The Feds and “Libertarian Paternalism”
The Anti-Phillips Curve
Status, Spite, Envy, and Income Redistribution
Economics: The Dismal (Non) Science
A Further Note about “Libertarian” Paternalism
Apropos Paternalism
Where’s My Nobel?
Toward a Capital Theory of Value
The Laffer Curve, “Fiscal Responsibility,” and Economic Growth
Stability Isn’t Everything
Income and Diminishing Marginal Utility
What Happened to Personal Responsibility?
The Causes of Economic Growth
Economic Growth since WWII
A Short Course in Economics
Addendum to a Short Course in Economics
Monopoly: Private Is Better than Public
The “Big Five” and Economic Performance
Does the Minimum Wage Increase Unemployment?
Rationing and Health Care
The Perils of Nannyism: The Case of Obamacare
More about the Perils of Obamacare
Health-Care Reform: The Short of It
Toward a Risk-Free Economy
Enough of “Social Welfare”
A True Flat Tax
The Case of the Purblind Economist
How the Great Depression Ended
Why Outsourcing Is Good: A Simple Lesson for “Liberal” Yuppies
Microeconomics and Macroeconomics
The Illusion of Prosperity and Stability
The Deficit Commission’s Deficit of Understanding
“Buy Local”
“Net Neutrality”
The Bowles-Simpson Report
The Bowles-Simpson Band-Aid
Competition Shouldn’t Be a Dirty Word
Subjective Value: A Proof by Example
The Stagnation Thesis
Taxing the Rich
More about Taxing the Rich
Money, Credit, and Economic Fluctuations
A Keynesian Fantasy Land
“Tax Expenditures” Are Not Expenditures
The Keynesian Fallacy and Regime Uncertainty
Does “Pent Up” Demand Explain the Post-War Recovery?
Creative Destruction, Reification, and Social Welfare
What Free-Rider Problem?
Why the “Stimulus” Failed to Stimulate
The Arrogance of (Some) Economists
The “Jobs Speech” That Obama Should Have Given
Say’s Law, Government, and Unemployment
Regime Uncertainty and the Great Recession
Regulation as Wishful Thinking
Extreme Economism
We Owe It to Ourselves
In Defense of the 1%
Lay My (Regulatory) Burden Down
Irrational Rationality
The Burden of Government
Economic Growth Since World War II
The Rationing Fallacy
Government in Macroeconomic Perspective
Keynesianism: Upside-Down Economics in the Collectivist Cause
How High Should Taxes Be?
The 80-20 Rule, Illustrated
Economic Horror Stories: The Great “Demancipation” and Economic Stagnation
Baseball Statistics and the Consumer Price Index
Why Are Interest Rates So Low?
Vulgar Keynesianism and Capitalism
America’s Financial Crisis Is Now
“Ensuring America’s Freedom of Movement”: A Review
“Social Insurance” Isn’t Insurance — Nor Is Obamacare
The Keynesian Multiplier: Phony Math
The True Multiplier
Discounting in the Public Sector
Some Inconvenient Facts about Income Inequality
Mass (Economic) Hysteria: Income Inequality and Related Themes
Social Accounting: A Tool of Social Engineering
Playing the Social Security Trust Fund Shell Game
Income Inequality and Economic Growth
A Case for Redistribution, Not Made
McCloskey on Piketty
The Rahn Curve Revisited
The Slow-Motion Collapse of the Economy
Nature, Nurture, and Inequality
Understanding Investment Bubbles
The Real Burden of Government
Diminishing Marginal Utility and the Redistributive Urge
Capitalism, Competition, Prosperity, and Happiness
Further Thoughts about the Keynesian Multiplier


VI. Humor, Satire, and Wry Commentary
Political Parlance
Some Management Tips
Ten-Plus Commandments of Liberalism, er, Progressivism
To Pay or Not to Pay
The Ghost of Impeachments Past Presents “The Trials of William Jefferson Whatsit”
Getting It Perfect
His Life As a Victim
Bah, Humbug!
PC Madness
The Seven Faces of Blogging
Trans-Gendered Names
More Names
Stuff White (Liberal Yuppie) People Like
Driving and Politics
“Men’s Health”
I’ve Got a LIttle List
Driving and Politics (2)
A Sideways Glance at Military Strategy
A Sideways Glance at the Cabinet
A Sideways Glance at Politicians’ Memoirs
The Madness Continues


VII. Infamous Thinkers and Political Correctness
Sunstein at the Volokh Conspiracy
More from Sunstein
Cass Sunstein’s Truly Dangerous Mind
An (Imaginary) Interview with Cass Sunstein
Professor Krugman Flunks Economics
Peter Singer’s Fallacy
Slippery Sunstein
Sunstein and Executive Power
Nock Reconsidered
In Defense of Ann Coulter
Goodbye, Mr. Pitts
Our Miss Brooks
How to Combat Beauty-ism
The Politically Correct Cancer: Another Weapon in the War on Straight White Males
Asymmetrical (Ideological) Warfare
Social Justice
Peter Presumes to Preach
More Social Justice
Luck-Egalitarianism and Moral Luck
Empathy Is Overrated
In Defense of Wal-Mart
An Economist’s Special Pleading: Affirmative Action for the Ugly
Another Entry in the Sunstein Saga
Obesity and Statism (Richard Posner)
Obama’s Big Lie
The Sunstein Effect Is Alive and Well in the White House
Political Correctness vs. Civility
IQ, Political Correctness, and America’s Present Condition
Sorkin’s Left-Wing Propaganda Machine
Baseball or Soccer? David Brooks Misunderstands Life
Sunstein the Fatuous
Good Riddance
The Gaystapo at Work
The Gaystapo and Islam
The Perpetual Nudger


VIII. Intelligence and Psychology
Conservatism, Libertarianism, and “The Authoritarian Personality”
The F Scale, Revisited
The Psychologist Who Played God
Intelligence, Personality, Politics, and Happiness
Intelligence as a Dirty Word
Intelligence and Intuition
Nonsense about Presidents, IQ, and War
IQ, Political Correctness, and America’s Present Condition
Greed, Conscience, and Big Government
Privilege, Power, and Hypocrisy


IX. Justice
I’ll Never Understand the Insanity Defense
Does Capital Punishment Deter Homicide?
Libertarian Twaddle about the Death Penalty
A Crime Is a Crime
Crime and Punishment
Abortion and Crime
Saving the Innocent?
Saving the Innocent?: Part II
A Useful Precedent
More on Abortion and Crime
More Punishment Means Less Crime
More About Crime and Punishment
More Punishment Means Less Crime: A Footnote
Clear Thinking about the Death Penalty
Let the Punishment Fit the Crime
Cell Phones and Driving: Liberty vs. Life
Another Argument for the Death Penalty
Less Punishment Means More Crime
Crime, Explained
Clear Thinking about the Death Penalty
What Is Justice?
Myopic Moaning about the War on Drugs
Saving the Innocent
Why Stop at the Death Penalty?
A Case for Perpetual Copyrights and Patents
The Least Evil Option
Legislating Morality
Legislating Morality (II)
Round Up the Usual Suspects
Left-Libertarians, Obama, and the Zimmerman Case
Free Will, Crime, and Punishment
Stop, Frisk, and Save Lives
Poverty, Crime, and Big Government
Crime Revisited
A Cop-Free World?


X. Libertarianism and Other Political Philosophies
The Roots of Statism in the United States
Libertarian-Conservatives Are from the Earth, Liberals Are from the Moon
Modern Utilitarianism
The State of Nature
Libertarianism and Conservatism
Judeo-Christian Values and Liberty
Redefining Altruism
Fundamentalist Libertarians, Anarcho-Capitalists, and Self-Defense
Where Do You Draw the Line?
Moral Issues
A Paradox for Libertarians
A Non-Paradox for Libertarians
Religion and Liberty
Science, Evolution, Religion, and Liberty
Whose Incompetence Do You Trust?
Enough of Altruism
Thoughts That Liberals Should Be Thinking
More Thoughts That Liberals Should Be Thinking
The Corporation and the State
Libertarianism and Preemptive War: Part II
Anarchy: An Empty Concept
The Paradox of Libertarianism
Privacy: Variations on the Theme of Liberty
The Fatal Naïveté of Anarcho-Libertarianism
Liberty as a Social Construct
This Is Objectivism?
Social Norms and Liberty (a reference page)
Social Norms and Liberty (a followup post)A Footnote about Liberty and the Social Compact
The Adolescent Rebellion Syndrome
Liberty and Federalism
Finding Liberty
Nock Reconsidered
The Harm Principle
Footnotes to “The Harm Principle”
The Harm Principle, Again
Rights and Cosmic Justice
Liberty, Human Nature, and the State
Idiotarian Libertarians and the Non-Aggression Principle
Slopes, Ratchets, and the Death Spiral of Liberty
Postive Rights and Cosmic Justice: Part I
Positive Rights and Cosmic Justice: Part II
The Case against Genetic Engineering
Positive Rights and Cosmic Justice: Part III
A Critique of Extreme Libertarianism
Libertarian Whining about Cell Phones and Driving
The Golden Rule, for Libertarians
Positive Rights and Cosmic Justice: Part IV
Anarchistic Balderdash
Compare and Contrast
Irrationality, Suboptimality, and Voting
Wrong, Wrong, Wrong
The Political Case for Traditional Morality
Compare and Contrast, Again
Pascal’s Wager, Morality, and the State
The Fear of Consequentialism
Optimality, Liberty, and the Golden Rule
The People’s Romance
Objectivism: Tautologies in Search of Reality
Morality and Consequentialism
On Liberty
Greed, Cosmic Justice, and Social Welfare
Positive Rights and Cosmic Justice
Fascism with a “Friendly” Face
Democracy and Liberty
The Interest-Group Paradox
Inventing “Liberalism”
Civil Society and Homosexual “Marriage”
What Is Conservatism?
Utilitarianism vs. Liberty
Fascism and the Future of America
The Indivisibility of Economic and Social Liberty
Law and Liberty
Negative Rights
Negative Rights, Social Norms, and the Constitution
Tocqueville’s Prescience
Accountants of the Soul
Invoking Hitler
The Unreality of Objectivism
“Natural Rights” and Consequentialism
Rawls Meets Bentham
The Left
Our Enemy, the State
Pseudo-Libertarian Sophistry vs. True Libertarianism
What Are “Natural Rights”?
The Golden Rule and the State
Libertarian Conservative or Conservative Libertarian?
Bounded Liberty: A Thought Experiment
Evolution, Human Nature, and “Natural Rights”
More Pseudo-Libertarianism
The Meaning of Liberty
Positive Liberty vs. Liberty
On Self-Ownership and Desert
Understanding Hayek
Corporations, Unions, and the State
Facets of Liberty
Burkean Libertarianism
Rights: Source, Applicability, How Held
What Is Libertarianism?
Nature Is Unfair
True Libertarianism, One More Time
Human Nature, Liberty, and Rationalism
Utilitarianism and Psychopathy
A Declaration and Defense of My Prejudices about Governance
Libertarianism and Morality
Libertarianism and Morality: A Footnote
What Is Bleeding-Heart Libertarianism?
Liberty, Negative Rights, and Bleeding Hearts
Cato, the Kochs, and a Fluke
Why Conservatism Works
A Man for No Seasons
Bleeding-Heart Libertarians = Left-Statists
Not Guilty of Libertarian Purism
Liberty and Society
Tolerance on the Left
The Eclipse of “Old America”
Genetic Kinship and Society
Liberty as a Social Construct: Moral Relativism?
Defending Liberty against (Pseudo) Libertarians
The Fallacy of the Reverse-Mussolini Fallacy
Defining Liberty
Getting It Almost Right
The Social Animal and the “Social Contract”
The Futile Search for “Natural Rights”
The Pseudo-Libertarian Temperament
Parsing Political Philosophy (II)
Modern Liberalism as Wishful Thinking
Getting Liberty Wrong
Romanticizing the State
Libertarianism and the State
Egoism and Altruism
My View of Libertarianism
Sober Reflections on “Charlie Hebdo”
“The Great Debate”: Not So Great
No Wonder Liberty Is Disappearing
The Principles of Actionable Harm
More About Social Norms and Liberty


XI. Politics, Politicians, and the Consequences of Government
Starving the Beast
Torture and Morality
Starving the Beast, Updated
Starving the Beast: Readings
Presidential Legacies
The Rational Voter?
FDR and Fascism
The “Southern Strategy”
An FDR Reader
The “Southern Strategy”: A Postscript
The Modern Presidency: A Tour of American History
Politicizing Economic Growth
The End of Slavery in the United States
I Want My Country Back
What Happened to the Permanent Democrat Majority?
More about the Permanent Democrat Majority
Undermining the Free Society
Government Failure: An Example
The Public-School Swindle
PolitiFact Whiffs on Social Security
The Destruction of Society in the Name of “Society”
About Democracy
Externalities and Statism
Taxes: Theft or Duty?
Society and the State
Don’t Use the “S” Word When the “F” Word Will Do
The Capitalist Paradox Meets the Interest-Group Paradox
Is Taxation Slavery?
A Contrarian View of Universal Suffrage
The Hidden Tragedy of the Assassination of Lincoln
America: Past, Present, and Future
IQ, Political Correctness, and America’s Present Condition
Progressive Taxation Is Alive and Well in the U.S. of A.
“Social Insurance” Isn’t Insurance — Nor Is Obamacare
“We the People” and Big Government
The Culture War
The Fall and Rise of American Empire
O Tempora O Mores!
Presidential Treason
A Home of One’s Own
The Criminality and Psychopathy of Statism
Surrender? Hell No!
Social Accounting: A Tool of Social Engineering
Playing the Social Security Trust Fund Shell Game
Two-Percent Tyranny
A Sideways Glance at Public “Education”
Greed, Conscience, and Big Government
The Many-Sided Curse of Very Old Age
The Slow-Motion Collapse of the Economy
How to Eradicate the Welfare State, and How Not to Do It
“Blue Wall” Hype
Does Obama Love America?
Obamanomics in Action
Democracy, Human Nature, and the Future of America
1963: The Year Zero


XII. Science, Religion, and Philosophy
Same Old Story, Same Old Song and Dance
Atheism, Religion, and Science
The Limits of Science
Beware of Irrational Atheism
The Creation Model
Free Will: A Proof by Example?
Science in Politics, Politics in Science
Evolution and Religion
Science, Evolution, Religion, and Liberty
What’s Wrong with Game Theory
Is “Nothing” Possible?
Pseudo-Science in the Service of Political Correctness
Science’s Anti-Scientific Bent
Science, Axioms, and Economics
The Purpose-Driven Life
The Tenth Dimension
The Universe . . . Four Possibilities
Atheism, Religion, and Science Redux
“Warmism”: The Myth of Anthropogenic Global Warming
More Evidence against Anthropogenic Global Warming
Yet More Evidence against Anthropogenic Global Warming
Pascal’s Wager, Morality, and the State
Achilles and the Tortoise: A False Paradox
The Greatest Mystery
Modeling Is Not Science
Freedom of Will and Political Action
Fooled by Non-Randomness
Randomness Is Over-Rated
Anthropogenic Global Warming Is Dead, Just Not Buried Yet
Beware the Rare Event
Landsburg Is Half-Right
What Is Truth?
The Improbability of Us
Wrong Again
More Thoughts about Evolutionary Teleology
A Digression about Probability and Existence
Evolution and the Golden Rule
A Digression about Special Relativity
More about Probability and Existence
Existence and Creation
Probability, Existence, and Creation
Temporal and Spatial Agreement
In Defense of Subjectivism
The Atheism of the Gaps
The Ideal as a False and Dangerous Standard
Demystifying Science
Religion on the Left
Analysis for Government Decision-Making: Hemi-Science, Hemi-Demi-Science, and Sophistry
Scientism, Evolution, and the Meaning of Life
Luck and Baseball, One More Time
Are the Natural Numbers Supernatural?
The Candle Problem: Balderdash Masquerading as Science
Mysteries: Sacred and Profane
More about Luck and Baseball
Combinatorial Play
Something from Nothing?
Pseudoscience, “Moneyball,” and Luck
Something or Nothing
Understanding the Monty Hall Problem
My Metaphysical Cosmology
Further Thoughts about Metaphysical Cosmology
The Fallacy of Human Progress
The Glory of the Human Mind
Pinker Commits Scientism
Spooky Numbers, Evolution, and Intelligent Design
AGW: The Death Knell
Mind, Cosmos, and Consciousness
The Limits of Science (II)
Not Over the Hill
The Pretence of Knowledge
“The Science Is Settled”
The Compleat Monty Hall Problem
“Settled Science” and the Monty Hall Problem
Evolution, Culture, and “Diversity”
Some Thoughts about Probability
Rationalism, Empiricism, and Scientific Knowledge
AGW in Austin?


XIII. Self-Ownership (abortion, euthanasia, marriage, and other aspects of the human condition)
Feminist Balderdash
Libertarianism, Marriage, and the True Meaning of Family Values
Law, Liberty, and Abortion
Privacy, Autonomy, and Responsibility
Parenting, Religion, Culture, and Liberty
The Case against Genetic Engineering
A “Person” or a “Life”?
A Wrong-Headed Take on Abortion
In Defense of Marriage
Crimes against Humanity
Abortion and Logic
The Myth That Same-Sex “Marriage” Causes No Harm
Abortion, Doublethink, and Left-Wing Blather
Abortion, “Gay Rights,” and Liberty
Dan Quayle Was (Almost) Right
The Most Disgusting Thing I’ve Read Today
Posner the Fatuous
Marriage: Privatize It and Revitalize It


XIV. War and Peace
Getting It Wrong: Civil Libertarians and the War on Terror (A Case Study)
Libertarian Nay-Saying on Foreign and Defense Policy, Revisited
Right On! For Libertarian Hawks Only
Understanding Libertarian Hawks
Defense, Anarcho-Capitalist Style
The Illogic of Knee-Jerk Civil Liberties Advocates
Getting It All Wrong about the Risk of Terrorism
Conservative Revisionism, Conservative Backlash, or Conservative Righteousness?
But Wouldn’t Warlords Take Over?
Sorting Out the Libertarian Hawks and Doves
Shall We All Hang Separately?
September 11: A Remembrance
September 11: A Postscript for “Peace Lovers”
Give Me Liberty or Give Me Non-Aggression?
NSA “Eavesdropping”: The Last Word (from Me)
Riots, Culture, and the Final Showdown
Thomas Woods and War
In Which I Reply to the Executive Editor of The New York Times
“Peace for Our Time”
Taking on Torture
Conspiracy Theorists’ Cousins
September 11: Five Years On
How to View Defense Spending
The Best Defense . . .
A Skewed Perspective on Terrorism
Not Enough Boots: The Why of It
Here We Go Again
“The War”: Final Grade
Torture, Revisited
Waterboarding, Torture, and Defense
Liberalism and Sovereignty
The Media, the Left, and War
Getting It Wrong and Right about Iran
The McNamara Legacy: A Personal Perspective
The “Predator War” and Self-Defense
The National Psyche and Foreign Wars
A Moralist’s Moral Blindness
A Grand Strategy for the United States
The Folly of Pacifism
Rating America’s Wars
Transnationalism and National Defense
The Next 9/11?
The Folly of Pacifism, Again
September 20, 2001: Hillary Clinton Signals the End of “Unity”
Patience as a Tool of Strategy
The War on Terror, As It Should Have Been Fought
The Cuban Missile Crisis, Revisited
Preemptive War
Preemptive War and Iran
Some Thoughts and Questions about Preemptive War
Defense as an Investment in Liberty and Prosperity
Riots, Culture, and the Final Showdown (revisited)
The Barbarians Within and the State of the Union
The World Turned Upside Down
Utilitarianism and Torture
Defense Spending: One More Time
Walking the Tightrope Reluctantly
The President’s Power to Kill Enemy Combatants


XV. Writing and Language
“Hopefully” Arrives
Hopefully, This Post Will Be Widely Read
Why Prescriptivism?
A Guide to the Pronunciation of General American English
On Writing (a comprehensive essay about writing, which covers some of the material presented in other posts in this section)


Not-So-Random Thoughts (XV)

Links to the other posts in this occasional series may be found at “Favorite Posts,” just below the list of topics.

*     *     *

Victor Davis Hanson writes:

This descent into the Dark Ages will not end well. It never has in the past. [“Building the New Dark-Age Mind,” Works and Days, June 8, 2015]

Hamson’s chronicle of political correctness and doublespeak echoes one theme of my post, “1963: The Year Zero.”

*     *     *

Timothy Taylor does the two-handed economist act:

It may be that the question of “does inequality slow down economic growth” is too broad and diffuse to be useful. Instead, those of us who care about both the rise in inequality and the slowdown in economic growth should be looking for policies to address both goals, without presuming that substantial overlap will always occur between them. [“Does Inequality Reduce Economic Growth: A Skeptical View,” The Conversible Economist, May 29, 2015]

The short answer to the question “Does inequality reduce growth?” is no. See my post “Income Inequality and Economic Growth.” Further, even if inequality does reduce growth, the idea of reducing inequality (through income redistribution, say) to foster growth is utilitarian and therefore morally egregious. (See “Utilitarianism vs. Liberty.”)

*     *     *

In “Diminishing Marginal Utility and the Redistributive Urge” I write:

[L]eftists who deign to offer an economic justification for redistribution usually fall back on the assumption of the diminishing marginal utility (DMU) of income and wealth. In doing so, they commit (at least) four errors.

The first error is the fallacy of misplaced concreteness which is found in the notion of utility. Have you ever been able to measure your own state of happiness? I mean measure it, not just say that you’re feeling happier today than you were when your pet dog died. It’s an impossible task, isn’t it? If you can’t measure your own happiness, how can you (or anyone) presume to measure and aggregate the happiness of millions or billions of individual human beings? It can’t be done.

Which brings me to the second error, which is an error of arrogance. Given the impossibility of measuring one person’s happiness, and the consequent impossibility of measuring and comparing the happiness of many persons, it is pure arrogance to insist that “society” would be better off if X amount of income or wealth were transferred from Group A to Group B….

The third error lies in the implicit assumption embedded in the idea of DMU. The assumption is that as one’s income or wealth rises one continues to consume the same goods and services, but more of them….

All of that notwithstanding, the committed believer in DMU will shrug and say that at some point DMU must set in. Which leads me to the fourth error, which is an error of introspection….  [If over the years] your real income has risen by a factor of two or three or more — and if you haven’t messed up your personal life (which is another matter) — you’re probably incalculably happier than when you were just able to pay your bills. And you’re especially happy if you put aside a good chunk of money for your retirement, the anticipation and enjoyment of which adds a degree of utility (such a prosaic word) that was probably beyond imagining when you were in your twenties, thirties, and forties.

Robert Murphy agrees:

[T]he problem comes in when people sometimes try to use the concept of DMU to justify government income redistribution. Specifically, the argument is that (say) the billionth dollar to Bill Gates has hardly any marginal utility, while the 10th dollar to a homeless man carries enormous marginal utility. So clearly–the argument goes–taking a dollar from Bill Gates and giving it to a homeless man raises “total social utility.”

There are several serious problems with this type of claim. Most obvious, even if we thought it made sense to attribute units of utility to individuals, there is no reason to suppose we could compare them across individuals. For example, even if we thought a rich man had units of utility–akin to the units of his body temperature–and that the units declined with more money, and likewise for a poor person, nonetheless we have no way of placing the two types of units on the same scale….

In any event, this is all a moot point regarding the original question of interpersonal utility comparisons. Even if we thought individuals had cardinal utilities, it wouldn’t follow that redistribution would raise total social utility.

Even if we retreat to the everyday usage of terms, it still doesn’t follow as a general rule that rich people get less happiness from a marginal dollar than a poor person. There are many people, especially in the financial sector, whose self-esteem is directly tied to their earnings. And as the photo indicates, Scrooge McDuck really seems to enjoy money. Taking gold coins from Scrooge and giving them to a poor monk would not necessarily increase happiness, even in the everyday psychological sense. [“Can We Compare People’s Utilities?,” Mises Canada, May 22, 2015]

See also David Henderson’s “Murphy on Interpersonal Utility Comparisons” (EconLog, May 22, 2015) and Henderson’s earlier posts on the subject, to which he links. Finally, see my comment on an earlier post by Henderson, in which he touches on the related issue of cost-benefit analysis.

*     *     *

Here’s a slice of what Robert Tracinski has to say about “reform conservatism”:

The key premise of this non-reforming “reform conservatism” is the idea that it’s impossible to really touch the welfare state. We might be able to alter its incentives and improve its clanking machinery, but only if we loudly assure everyone that we love it and want to keep it forever.

And there’s the problem. Not only is this defeatist at its core, abandoning the cause of small government at the outset, but it fails to address the most important problem facing the country.

“Reform conservatism” is an answer to the question: how can we promote the goal of freedom and small government—without posing any outright challenge to the welfare state? The answer: you can’t. All you can do is tinker around the edges of Leviathan. And ultimately, it won’t make much difference, because it will all be overwelmed in the coming disaster. [“Reform Conservatism Is an Answer to the Wrong Question,” The Federalist, May 22, 2015]

Further, as I observe in “How to Eradicate the Welfare State, and How Not to Do It,” the offerings of “reform conservatives”

may seem like reasonable compromises with the left’s radical positions. But they are reasonable compromises only if you believe that the left wouldn’t strive vigorously to undo them and continue the nation’s march toward full-blown state socialism. That’s the way leftists work. They take what they’re given and then come back for more, lying and worse all the way.

See also Arnold Kling’s “Reason Roundtable on Reform Conservatism” (askblog, May 22, 2015) and follow the links therein.

*     *     *

I’ll end this installment with a look at science and the anti-scientific belief in catastrophic anthropogenic global warming.

Here’s Philip Ball in “The Trouble With Scientists“:

It’s likely that some researchers are consciously cherry-picking data to get their work published. And some of the problems surely lie with journal publication policies. But the problems of false findings often begin with researchers unwittingly fooling themselves: they fall prey to cognitive biases, common modes of thinking that lure us toward wrong but convenient or attractive conclusions. “Seeing the reproducibility rates in psychology and other empirical science, we can safely say that something is not working out the way it should,” says Susann Fiedler, a behavioral economist at the Max Planck Institute for Research on Collective Goods in Bonn, Germany. “Cognitive biases might be one reason for that.”

Psychologist Brian Nosek of the University of Virginia says that the most common and problematic bias in science is “motivated reasoning”: We interpret observations to fit a particular idea. Psychologists have shown that “most of our reasoning is in fact rationalization,” he says. In other words, we have already made the decision about what to do or to think, and our “explanation” of our reasoning is really a justification for doing what we wanted to do—or to believe—anyway. Science is of course meant to be more objective and skeptical than everyday thought—but how much is it, really?

Whereas the falsification model of the scientific method championed by philosopher Karl Popper posits that the scientist looks for ways to test and falsify her theories—to ask “How am I wrong?”—Nosek says that scientists usually ask instead “How am I right?” (or equally, to ask “How are you wrong?”). When facts come up that suggest we might, in fact, not be right after all, we are inclined to dismiss them as irrelevant, if not indeed mistaken….

Given that science has uncovered a dizzying variety of cognitive biases, the relative neglect of their consequences within science itself is peculiar. “I was aware of biases in humans at large,” says [Chris] Hartgerink [of Tilburg University in the Netherlands], “but when I first ‘learned’ that they also apply to scientists, I was somewhat amazed, even though it is so obvious.”…

One of the reasons the science literature gets skewed is that journals are much more likely to publish positive than negative results: It’s easier to say something is true than to say it’s wrong. Journal referees might be inclined to reject negative results as too boring, and researchers currently get little credit or status, from funders or departments, from such findings. “If you do 20 experiments, one of them is likely to have a publishable result,” [Ivan] Oransky and [Adam] Marcus [who run the service Retraction Watch] write. “But only publishing that result doesn’t make your findings valid. In fact it’s quite the opposite.”9 [Nautilus, May 14, 2015]

Zoom to AGW. Robert Tracinski assesses the most recent bit of confirmation bias:

A lot of us having been pointing out one of the big problems with the global warming theory: a long plateau in global temperatures since about 1998. Most significantly, this leveling off was not predicted by the theory, and observed temperatures have been below the lowest end of the range predicted by all of the computerized climate models….

Why, change the data, of course!

Hence a blockbuster new report: a new analysis of temperature data since 1998 “adjusts” the numbers and magically finds that there was no plateau after all. The warming just continued….

How convenient.

It’s so convenient that they’re signaling for everyone else to get on board….

This is going to be the new party line. “Hiatus”? What hiatus? Who are you going to believe, our adjustments or your lying thermometers?…

The new adjustments are suspiciously convenient, of course. Anyone who is touting a theory that isn’t being borne out by the evidence and suddenly tells you he’s analyzed the data and by golly, what do you know, suddenly it does support his theory—well, he should be met with more than a little skepticism.

If we look, we find some big problems. The most important data adjustments by far are in ocean temperature measurements. But anyone who has been following this debate will notice something about the time period for which the adjustments were made. This is a time in which the measurement of ocean temperatures has vastly improved in coverage and accuracy as a whole new set of scientific buoys has come online. So why would this data need such drastic “correcting”?

As climatologist Judith Curry puts it:

The greatest changes in the new NOAA surface temperature analysis is to the ocean temperatures since 1998. This seems rather ironic, since this is the period where there is the greatest coverage of data with the highest quality of measurements–ARGO buoys and satellites don’t show a warming trend. Nevertheless, the NOAA team finds a substantial increase in the ocean surface temperature anomaly trend since 1998.


I realize the warmists are desperate, but they might not have thought through the overall effect of this new “adjustment” push. We’ve been told to take very, very seriously the objective data showing global warming is real and is happening—and then they announce that the data has been totally changed post hoc. This is meant to shore up the theory, but it actually calls the data into question….

All of this fits into a wider pattern: the global warming theory has been awful at making predictions about the data ahead of time. But it has been great at going backward, retroactively reinterpreting the data and retrofitting the theory to mesh with it. A line I saw from one commenter, I can’t remember where, has been rattling around in my head: “once again, the theory that predicts nothing explains everything.” [“Global Warming: The Theory That Predicts Nothing and Explains Everything,” The Federalist, June 8, 2015]

Howard Hyde also weighs in with “Climate Change: Where Is the Science?” (American Thinker, June 11, 2015).

Bill Nye, the so-called Science Guy, seems to epitomize the influence of ideology on “scientific knowledge.”  I defer to John Derbyshire:

Bill Nye the Science Guy gave a commencement speech at Rutgers on Sunday. Reading the speech left me thinking that if this is America’s designated Science Guy, I can be the nation’s designated swimsuit model….

What did the Science Guy have to say to the Rutgers graduates? Well, he warned them of the horrors of climate change, which he linked to global inequality.

We’re going to find a means to enable poor people to advance in their societies in countries around the world. Otherwise, the imbalance of wealth will lead to conflict and inefficiency in energy production, which will lead to more carbon pollution and a no-way-out overheated globe.

Uh, given that advanced countries use far more energy per capita than backward ones—the U.S.A. figure is thirty-four times Bangladesh’s—wouldn’t a better strategy be to keep poor countries poor? We could, for example, encourage all their smartest and most entrepreneurial people to emigrate to the First World … Oh, wait: we already do that.

The whole climate change business is now a zone of hysteria, generating far more noise—mostly of a shrieking kind—than its importance justifies. Opinions about climate change are, as Greg Cochran said, “a mark of tribal membership.” It is also the case, as Greg also said, that “the world is never going to do much about in any event, regardless of the facts.”…

When Ma Nature means business, stuff happens on a stupendously colossal scale.  And Bill Nye the Science Guy wants Rutgers graduates to worry about a 0.4ºC warming over thirty years? Feugh.

The Science Guy then passed on from the dubiously alarmist to the batshit barmy.

There really is no such thing as race. We are one species … We all come from Africa.

Where does one start with that? Perhaps by asserting that: “There is no such thing as states. We are one country.”

The climatological equivalent of saying there is no such thing as race would be saying that there is no such thing as weather. Of course there is such a thing as race. We can perceive race with at least three of our five senses, and read it off from the genome. We tick boxes for it on government forms: I ticked such a box for the ATF just this morning when buying a gun.

This is the Science Guy? The foundational text of modern biology bears the title On the Origin of Species by Means of Natural Selection, or the Preservation of Favored Races in the Struggle for Life. Is biology not a science?

Darwin said that populations of a species long separated from each other will diverge in their biological characteristics, forming races. If the separation goes on long enough, any surviving races will diverge all the way to separate species. Was Ol’ Chuck wrong about that, Mr. Science Guy?

“We are one species”? Rottweilers and toy poodles are races within one species, a species much newer than ours; yet they differ mightily, not only in appearance but also—gasp!—in behavior, intelligence, and personality. [“Nye Lied, I Sighed,” Taki’s Magazine, May 21, 2015]

This has gone on long enough. Instead of quoting myself, I merely refer you to several related posts:

Demystifying Science
AGW: The Death Knell
Evolution and Race
The Limits of Science (II)
The Pretence of Knowledge
“The Science Is Settled”
The Limits of Science, Illustrated by Scientists
Rationalism, Empiricism, and Scientific Knowledge
AGW in Austin?


AGW in Austin?

“Climate change” is religion refracted through the lens of paganism.

Melanie Phillips

There is a hypothesis that the purported rise in global temperatures since 1850 (or some shorter span if you’re embarrassed by periods of notable decline after 1850) was or is due mainly or solely to human activity, as manifested in emissions of CO2. Adherents of this hypothesis call the supposed phenomenon by various names: anthropogenic global warming (AGW), just plain global warming, climate change, and climate catastrophe, for example.

Those adherents loudly advocate measures that (they assert) would reduce CO2 emissions by enough to avoid climatic catastrophe. They have been advocating such measures for about 25 years, yet climate catastrophe remains elusive. (See “pause,” below.) But the true believers in AGW remain steadfast in their faith.

Actually, belief in catastrophic AGW requires three leaps of faith. The first leap is to assume the truth of the alternative hypothesis — a strong and persistent connection between CO2 emissions and global temperatures — without having found (or even looked for) scientific evidence which disproves the null hypothesis, namely, that there isn’t a strong and persistent connection between CO2 emissions and global temperatures. The search for such evidence shouldn’t be confined to the near-past, but should extend centuries, millennia, and eons into the past. The problem for advocates of AGW is that a diligent search of that kind works against the alternative hypothesis and supports the null hypothesis. As a result, the advocates of AGW confine their analysis to the recent past and substitute kludgy computer models, full of fudge-factors, for a disinterested examination of the actual causes of climate change. There is strong evidence that such causes include solar activity and its influence on cloud formation through cosmic radiation. That truth is too inconvenient for the AGW mob, as are many other truths about climate.

The second leap of faith is to assume that rising temperatures, whatever the cause, are a bad thing. This, despite the known advantages of warmer climates: longer growing seasons and lower death rates, to name but two. This is so because believers in AGW and policies that would (according to them) mitigate it, like to depict worst-case scenarios about the extent of global warming and its negative effects.

The third leap of faith is related to the first two. It is the belief that policies meant to mitigate global warming — policies that mainly involve the curtailment of CO2 emissions — would be (a) effective and (b) worth the cost. There is more than ample doubt about both propositions, which seem to flow from the kind of anti-scientific mind that eagerly embraces the alternative hypothesis without first having disproved the null hypothesis. It is notable that “worth the cost” is a value judgment which springs readily from the tongues and keyboards of affluent Westerners like __________ who already have it made. (Insert “Al Gore”, “high-end Democrats,” “liberal pundits and politicians,” etc.)

Prominent among the leapers-of-faith in my neck of the woods is the “chief weathercaster” of an Austin TV station. We watch his weather forecasts because he spews out more information than his competitors, but I must resist the urge to throw a brick through my TV screen when his mask slips and he reveals himself as a true believer in AGW. What else should I expect from a weather nazi who proclaims it “nice” when daytime high temperatures are in the 60s and 70s, and who bemoans higher temperatures?

Like any nazi, he projects his preferences onto others — in this case his viewership. This undoubtedly includes a goodly number of persons (like me) who moved to Austin and stay in Austin for the sake of sunny days when the thermometer is in the 80-to-95-degree range. It is a bit much when temperatures are consistently in the high 90s and low 100s, as they are for much of Austin’s summer. But that’s the price of those sunny days in the 80s and low 90s, unless you can afford to live in San Diego or Hawaii instead of Austin.

Anyway, the weather nazi would make a great deal out of the following graph:

12-month average temperatures in Austin_1977-2015

The graph covers the period from April 1977 through April 2015. The jagged line represents 12-month averages of monthly averages for the official National Weather Service stations in Austin: Mueller Airport (until July 1999) and Camp Mabry (July 1999 to the present). (There’s a history of Austin’s weather stations in a NOAA document, “Austin Climate Summary.”) The upward trend is unmistakeable. Equally unmistakeable is the difference between the early and late years of the period — a difference that’s highlighted by the y-error bars, which represent a span of plus-and-minus one standard deviation from the mean for the period.

Your first question should be “Why begin with April 1977?” Well, it’s a “good” starting point — if you want to sell AGW — because the 12-month average temperature as of April 1977 was the lowest in 64 years. After all, it was the seemingly steep increase in temperatures after 1970 that sparked the AGW business.

What about the “fact” that temperatures have been rising since about 1850? The “fact” is that temperatures have been recorded in a relatively small number of locales continuously since the 1850s, though the reliability of the temperature data and their relationship to any kind of “global” average is in serious doubt. The most reliable data come from weather satellites, and those have been in operation only since the late 1970s.

A recent post by Bob Tisdale, “New UAH Lower Troposphere Temperature Data Show No Global Warming for More Than 18 Years” (Watts Up With That?, April 29, 2015), summarizes the history of satellite readings, in the course of documenting the “pause” in global warming. The “pause,” if dated from 2001, has lasted 14 years; if dated from 1997, it has lasted 18 years. In either event, the “pause” has lasted about as long as the rise in late-20th century temperatures that led to the AGW hypothesis.

What about those observations since the 1850s? Riddled with holes, that’s what. And even if they were reliable and covered a good part of the globe (which they aren’t and don’t), they wouldn’t tell the story that AGW enthusiasts are trying to sell. Take Austin, for example, which has a (broken) temperature record dating back to 1856:

12-month average temperatures in Austin_1856-2015

Looks just like the first graph? No, it doesn’t. The trend line and error bars suggest a trend that isn’t there. Strip away the trend line and the error bars, and you see this:

12-month average temperatures in Austin_1856-2015_2

Which is what? There’s a rise in temperatures between the 1850s and the early 1890s, consistent with the gradual warming that followed the Little Ice Age. The gap between the early 1890s and mid-19naughts seems to have been marked by lower temperatures. It’s possible to find several mini-trends between the mid-19naughts and 1977, but the most obvious “trend” is a flat line for the entire period:

12-month average temperatures in Austin_1903-1977

Following the sudden jump between 1977 and 1980, the “trend remains almost flat through 1997, albeit at a slightly higher level:

12-month average temperatures in Austin_1980-1997

The sharpest upward trend really began after the very strong (and naturally warming) El Niño of 1997-1998:

12-month average temperatures in Austin_1997-2015

Oh, wait! It turns out that Austin’s sort-of hot-spell from 1998 to the present coincides with the “pause” in global warming:

The pause_from WUWT_20150429
Source: Bob Tisdale, “New UAH Lower Troposphere Temperature Data Show No Global Warming for More Than 18 Years,” Watts Up With That?, April 29, 2015.

What a revolting development this would be for our local weather nazi, if he could be bothered to acknowledge it. And if he did, he’d have to look beyond the egregious AGW hypothesis for an explanation of the warmer temperatures that he abhors. Where should he look? Here: the rapid increase in Austin’s population, combined with a drought.

The rapid increase in Austin’s population since 2000 probably has caused an acceleration of the urban heat-island (UHI) effect. This is known to inflate city temperatures above those in the surrounding countryside by several degrees.

What about drought? In Austin, the drought of recent years is far less severe than the drought of the 1950s, but temperatures have risen more in recent years than they did in the 1950s:

Indices of 5-year average precipitation and temperature

Why? Because Austin’s population is now six times greater than it was in the 1950s. The UHI effect has magnified the drought effect.

Conclusion: Austin’s recent hot weather has nothing to do with AGW. But don’t try to tell that to a weather nazi — or to the officials of the City of Austin, who lurch zombie-like onward in their pursuit of “solutions” to a non-problem.

*     *     *

Related reading:
U.S. climate page at WUWT
Articles about UHI at WUWT
Roy W. Spencer, “Global Urban Heat Island Effect Study – An Update,” WUWT, March 10, 2010
Anthony Watts, “UHI – Worse Than We Thought?,” WUWT, August 20, 2014
Christopher Monckton of Brenchley, “The Great Pause Lengthens Again,” WUWT, January 3, 2015
Anthony Watts, “Two New Papers Suggest Solar Activity Is a ‘Climate Pacemaker‘,” WUWT, January 9, 2015
John Hinderaker, “Was 2014 Really the Warmest Year Ever?,” PowerLine, January 16, 2015
Roy W. Spencer, John R. Christy, and William D. Braswell, “Version 6.0 of the UAH Temperature Dataset Released: New LT Trend = +0.11 C/decade,”, April 28, 2015
Bob Tisdale, “New UAH Lower Troposphere Temperature Data Show No Global Warming for More Than 18 Years,” WUWT, April 29, 2015
Patrick J. Michaels and Charles C. Knappenberger, “You Ought to Have a Look: Science Round Up—Less Warming, Little Ice Melt, Lack of Imagination,” Cato at Liberty, May 1, 2015
Mike Brakey, “151 Degrees Of Fudging…Energy Physicist Unveils NOAA’s “Massive Rewrite” Of Maine Climate History,” NoTricksZone, May 2, 2015 (see also David Archibald, “A Prediction Coming True?,” WUWT, May 4, 2015)
Christopher Monckton of Brenchley, “El Niño Has Not Yet Paused the Pause,” WUWT, May 4, 2015
Anthony J. Sadar and JoAnn Truchan, “Saul Alinsky, Climate Scientist,” American Thinker, May 4, 2015
Clyde Spencer, “Anthropogenic Global Warming and Its Causes,” WUWT, May 5, 2015
Roy W. Spencer, “Nearly 3,500 Days since Major Hurricane Strike … Despite Record CO2,”, May 8, 2015

Related posts:
AGW: The Death Knell (with many links to related readings and earlier posts)
Not-So-Random Thoughts (XIV) (second item)


Not-So-Random Thoughts (XIV)


Links to the other posts in this occasional series may be found at “Favorite Posts,” just below the list of topics.

*     *     *

Paul Mirengoff explores the similarities between Neville Chamberlain and Barack Obama; for example:

We see with Chamberlain the same curious dynamic present in the Obama presidency. At home, a tough-as-nails administration/political machine that takes no prisoners and rarely compromises; abroad, a feckless operation with a pattern of caving to belligerent adversaries. [Neville Chamberlain and Barack Obama: The Similarities Run Deep,” Powerline Blog, April 15, 2014]

See also John Hinderaker’s Powerline post, “Daniel Pipes: The Obama Doctrine Serves Up One Disaster After Another” (April 6, 2015), and a piece by Eileen F. Toplansky,”Obama’s Three Premises” (American Thinker, April 20, 2015).

What is Obama up to? For my take, see “Does Obama Love America?

*     *     *

If it were possible to convince a climate alarmist that he is wrong, Christopher Monckton of Brenchley is the man for the job:

What Evidence,” asks Ronald Bailey’s headline (, April 3, 2015), “Would Convince You That Man-Made Climate Change Is Real?

The answer: a rational, scientific case rooted in established theory and data would convince me that manmade climate change is a problem. That it is real is not in doubt, for every creature that breathes out emits CO2 and thus affects the climate.

The true scientific question, then, is not the fatuous question whether “Man-Made Climate Change Is Real” but how much global warming our sins of emission may cause, and whether that warming might be more a bad thing than a good thing.

However, Mr Bailey advances no rational case. What, then, are the elements of a rational, scientific case that our influence on the climate will prove dangerous unless the West completes its current self-shutdown?… [How to Convince a Climate Skeptic He’s Wrong,” Watts Up With That, April 9, 2015]

There follows a step-by-step dismantling of Mr. Bailey’s case for alarmism. Lord Monckton ends with this:

[I]f Mr Bailey does me the courtesy of reading the above, he will realize that temperatures are not rising by much, glacial ice-melt (if occurring) is on too small a scale to raise sea level by much, global sea ice extent shows little change in two generations, ditto northern-hemisphere snow cover, there has been little increase in rainfall and (according to the IPCC) little evidence for “stronger rainstorms”, and the ocean warming is so small that it falls within the considerable measurement error.

The evidence he adduces is questionable at best on every count. The Temple of Thermageddon will have to do better than that if it wants to convince us in the teeth of the evidence….

…[N]o rational scientific or economic case can be made for taking any action whatsoever today in a probably futile and certainly cost-ineffective attempt to make global warming that is not happening as predicted today go away the day after tomorrow.

The correct policy to address what is likely to prove a non-problem – and what, even if it were every bit as much of a problem as the tax-gobblers would wish, could not by even their most creative quantitative easing be cost-effectively solved by any attempt at mitigation – is to have the courage to do nothing now and adapt later if necessary.

The question is why, in the teeth of the scientific and economic evidence, nearly all of the global governing class were so easily taken in or bought out or both by the strange coalescence of powerful vested interests who have, until now, profited so monstrously by the biggest fraud in history at such crippling expense in lives and treasure to the rest of us, and at such mortal threat to the integrity and trustworthiness of science itself. [Ibid.]

My own modest effort to quell climate alarmism is summarized in “AGW: The Death Knell.”

*     *     *

Steve Sailer has some fun with the latest bit of experimental hocus-pocus by the intelligence-isn’t-heritable crowd, as interpreted by a reporter for The Washington Post:

In the last few years, there appears to have been a decision to blame racial differences in intelligence on differences in income level, although, of course, that’s not very plausible. That’s what people said way back in 1965, but then the federal Coleman Report of 1966 showed that affluent black students weren’t setting the world on fire academically on average, and vast amounts of data have accumulated validating the Coleman Report ever since.

But a half century later we’re back to asserting the same untested theories as in 1965….

Allow me to point out that a national newspaper has asked a couple of guys who know what they are talking about to punch holes in the latest bit of goodthink and, as of press time, the American public hasn’t dug up Hitler’s DNA and elected it President. So maybe we’re actually mature enough to discuss reality rather than lie all the time?…

Six decades from now, the Education Secretary of the hereditary Bush-Clinton Administration will be declaring the key periods for federal intervention are the eight months and 29 days before birth … but not a day sooner! [Charles Murray and James Thompson Asked Their Opinions in ‘Post’ Article on Brain Size; World Hasn’t Ended, Yet,” The Unz Review, April 15, 2015]

Along the way, Sailer links to Dr. James Thompson’s post about the article in question. There’s a followup post by Thompson, and this one is good, too. See also this post by Sailer.

Gregory Cochran has a related post (“Scanners Live in Vain,” West Hunter, March 31, 2015), where he says this about the paper and the reporting about it:

There is a new paper out in Nature Neuroscience,  mainly by Kimberly Noble, on socioeconomic variables and and brain structure:  Family income, parental education and brain structure in children and adolescents. They found that cortex area went up with income, although more slowly at high incomes.  Judging from their comments to the press, the authors think that being poor shrinks your brain.

Of course, since intelligence is highly heritable, and since people in higher social classes, or with high income, have higher average IQs (although not nearly as high as I would like), you would expect their kids to be, on average, smarter than kids from low-income groups (and have larger brains, since brain size is correlated with IQ) for genetic reasons.  But I guess the authors of this paper have never heard of  any of that – which raises the question, did they scan the brains of the authors?  Because that would have been interesting.  You can actually do microscopic MRI.

Even better, in talking to Nature, another researcher, Martha Farah,  mentions unpublished work that shows that the brain-size correlation with SES  is already there (in African-American kids) by age one month!

Of course, finding that the pattern already exists at the age of one month seriously weakens any idea that being poor shrinks the brain: most of the environmental effects you would consider haven’t even come into play in the first four weeks, when babies drink milk, sleep, and poop. Genetics affecting both parents and their children would make more sense, if the pattern shows up so early (and I’ll bet money that, if real,  it shows up well before one month);  but Martha Farah, and the reporter from Nature, Sara Reardon, ARE TOO FUCKING DUMB to realize this.

And John Ray points to this:

Quick thinkers are born not made, claim scientists.

They have discovered a link between our genes and the ability to remain mentally on the ball in later life.

It is the first time a genetic link has been shown to explain why some people have quick thinking skills.

Researchers identified a common genetic variant – changes in a person’s genetic code – related to how quickly a person is able to process new information. [Jenny Hope, “Quick Thinkers Are Born Not Made: The Speed at Which We Process New Information Is Written in Our Genes,”, April 16, 2015]

Dr. Ray links to the underlying studies, here.

I’ve probably said more than I should say about the heritability of intelligence in “Race and Reason: The Achievement Gap — Causes and Implications,” “Evolution and Race,” “‘Wading’ into Race, Culture, and IQ,” and “The Harmful Myth of Inherent Equality.”

*     *     *

Speaking of equality, or the lack thereof, Daniel Bier explains “How Piketty Manufactured Rising [Wealth] Inequality in 6 Steps” (Foundation for Economic Education, April 9, 2015):

Piketty’s chart on US wealth inequality displayed a trend that none of its original sources showed. Worst of all, he didn’t tell his readers that he had done any of this, much less explained his reasoning.

But now Magness has deconstructed the chart and shown, step by step, how Piketty tortured his sources into giving him the result he wanted to see….

If your methods can produce opposite results using the same sources, depending entirely on your subjective judgment, you’re not doing science — you’re doing a Choose Your Own Adventure story where you start from the conclusion and work backwards.

Now that you’ve seen how it’s done, you too can “piketty” your data and massage your narrative into selling 1.5 million books — that almost no one will actually read, but will be widely cited as justification for higher taxes nonetheless.

Committed leftists will ignore Piketty’s step back from extreme redistributionism, which I discussed in “Not-So-Random Thoughts (XIII).”

*     *     *

Committed leftists will lament the predicate of “Has Obamacare Turned Voters Against Sharing the Wealth?” (The New York Times, April 15, 2015). The author of the piece, Thomas B. Edsall (formerly of The Washington Post), clearly laments the possibility. (I do not, of course.) Edsall’s article is full of good news (for me); for example:

In 2006, by a margin of more than two to one, 69-28, those surveyed by Gallup said that the federal government should guarantee health care coverage for all citizens of the United States. By late 2014, however, Gallup found that this percentage had fallen 24 points to 45 percent, while the percentage of respondents who said health care is not a federal responsibility nearly doubled to 52 percent.

Edsall’s main worry seems to be how such a mood shift will help Republicans. Evidently, he doesn’t care about taxpayers, people who earn their income, or economic growth, which is inhibited by redistribution from “rich” to “poor.” But what else is new? Edsall is just another representative of the elite punditariat — a member of the “top” part of the left’s “top and bottom” coalition.

Edsall and his ilk should be worried. See, for example, “The Obamacare Effect: Greater Distrust of Government” (the title tells the tale) and “‘Blue Wall’ Hype” which debunks the idea that Democrats have a lock on the presidency.

*     *     *

The question of nature vs. nurture, which I touched on three entries earlier, is closely related to the question of innate ability vs. effort as the key to success in a field of endeavor. “Scott Alexander” of Slate Star Codex has written at length about innate ability vs. effort in two recent posts: “No Clarity Around Growth Mindset…Yet” and “I Will Never Have the Ability to Clearly Explain My Beliefs about Growth Mindset.” (That should be “to explain clearly.”)

This is from the first-linked post:

If you’re not familiar with it, growth mindset is the belief that people who believe ability doesn’t matter and only effort determines success are more resilient, skillful, hard-working, perseverant in the face of failure, and better-in-a-bunch-of-other-ways than people who emphasize the importance of ability. Therefore, we can make everyone better off by telling them ability doesn’t matter and only hard work does.

This is all twaddle, as “Alexander” shows, more or less, in his two very long posts. My essay on the subject is a lot shorter and easier to grasp: “The Harmful Myth of Inherent Equality.”

*     *     *


Obamacare, not unsurprisingly to me, has led to the rationing of health care, according to Bob Unruh’s “Obamacare Blocks Patients Paying for Treatment” (WND, March 6, 2014). And Aleyne Singer delivers “More Proof Obamacare Is Increasing Coverage but Not Access to Health Care” (The Daily Signal, December 9, 2014).

None of this should surprise anyone who thought about the economics of Obamacare, as I did in “Rationing and Health Care,” “The Perils of Nannyism: The Case of Obamacare,” “More about the Perils of Obamacare,” and “Health-Care Reform: The Short of It.”

*     *     *

Ben Bernanke asks “Why Are Interest Rates So Low?” (Ben Bernanke’s Blog, March 30, 2015). His answer? In so many words, business is bad, which means that the demand for capital financing is relatively weak. But in a followup post, “Why Are Interest Rates So Low, Part 2: Secular Stagnation” (Ben Bernanke’s Blog, March 31, 2015), Bernanke argues that the problem isn’t secular stagnation.

I agree that interest rates are low because the economy remains weak, despite some recovery from the nadir of the Great Recession. But, unlike Bernanke, I don’t expect the economy to make a full recovery — and I’m talking about real growth, not phony unemployment-rate recovery. Why Not? See “Obamanomics in Action” and “The Rahn Curve Revisited.” The economy will never grow to its potential as long as the dead hand of government continues to press down on it.


Rationalism, Empiricism, and Scientific Knowledge

Take a very large number, say, 1 quintillion. Written out, it looks like this: 1,000,000,000,000,000,000. It can also be expressed as 1018 or 10.E+18.

I doubt that any human being has ever discerned 1 quintillion discrete objects in a single moment. Including the constituents of all of the stars and planets, there may be more than 1 quintillion particles of matter in the visible portion of the sky on a clear night. But no person may reasonably claim to have seen all of those particles of matter as individual objects.

I doubt, further, that any human being has ever discerned 1 million  objects in a lifetime, even a very long lifetime. And if I’m wrong about that, it’s certainly possible to conjure a number high enough to be well beyond the experiential capacity of any human being; 101000, for instance.

Despite the impossibility of experiencing 101000 things, it is possible to write the number and to perform mathematical operations which involve the number. So, in some sense, very large numbers “exist.” But they exist only because human beings are capable of thinking of them. They are not “real” in the same way that a sky full of stars and planets is real.

Numbers and mathematics are rational constructs of the minds of human beings. Stars and planets are observed; that is, there is empirical evidence of their existence.

Thus there are two1 types of scientific knowledge: rational2 and empirical. They are related in the following ways:

1. Rational knowledge builds on empirical knowledge. Astronomical observations enabled Copernicus to devise a mathematical heliocentric model of the universe, which was an improvement on the geocentric model.

2. Empirical knowledge builds on rational knowledge. Observations aimed at verifying the heliocentric model led eventually to the discovery that the Sun is not at the center of the universe.

3. Empirical knowledge may affirm or contradict rational knowledge. Einstein’s general theory of relativity, which is given in a paper written in 1915, says that light is deflected (bent) by gravity. Astronomical observations made in 1919 affirmed the effect of gravity on light. Had the observations contradicted the postulated effect, the general theory (if any) might be markedly different than the one set forth in 1915. (A scientific theory is more than a hypothesis; it has been substantiated, though it always remains open to refutation.)

4. Rational knowledge may lead to empirical knowledge. One of the postulates that underlies Einstein’s special theory of relativity is the constancy of the speed of light; that is, the speed of light is independent of the motion of the source or the observer. This is unlike (for example) the speed of a ball that is thrown inside a moving train car, in the direction of the train car’s motion. An observer who is stationary relative to the train car will see the speed of the ball as the sum of (a) its speed relative to the thrower and (b) the speed of the train car relative to the observer. Einstein’s postulate, which drew on James Clerk Maxwell’s empirically based theory of electromagnetism, was subsequently verified experimentally.

These reflections lead me to four conclusions:

  • Knowledge is provisional. Human beings often don’t know what to make of the things that they perceive, and what they make of those things is often found to be wrong.
  • When it comes to science, rational and empirical knowledge are intertwined, and their effects are cumulative.
  • Rational knowledge that can’t be or hasn’t been put to an empirical test is merely a hypothesis. The hypothesis may be correct, but it doesn’t represent knowledge.
  • Empirical knowledge necessarily precedes rational knowledge because hypotheses draw on empirical knowledge and must be substantiated by empirical knowledge.3

*     *     *

Related reading:
Thomas M. Lennon and Shannon Dea, “Continental Rationalism,” Stanford Encyclopedia of Philosophy, April 14, 2012 (substantive revision)
Peter Markie, “Rationalism vs. Empiricism,” Stanford Encyclopedia of Philosophy, March 21, 2013 (substantive revision)

Related posts:
Hemibel Thinking
What Is Truth?
Demystifying Science
Are the Natural Numbers Supernatural?
Pinker Commits Scientism
The Limits of Science (II)
The Pretence of Knowledge
“The Science Is Settled”
The Limits of Science, Illustrated by Scientists

1. This post focuses on scientific knowledge and ignores other phenomena that are sometimes classified as branches of knowledge, such as emotional knowledge.

2. In this context, rational means by virtue of reason, not lucid or sane. The discussion of rational knowledge is restricted to knowledge that derives from and is a logical extension of observed phenomena, as in the example with which the post begins. I will not, in this post, deal with intuition, innate knowledge, or innate concepts, which are also treated under the heading of rational knowledge.

3. Unless it is true that human beings are born with certain kinds of knowledge, or with certain concepts that can be filled in by knowledge. The article by Markie treats these possibilities at some length.


Not-So-Random Thoughts (XIII)

Links to the other posts in this occasional series may be found at “Favorite Posts,” just below the list of topics.

*     *     *

Jeremy Egerer says this “In Defense of a Beautiful Boss” (American Thinker, February 8, 2015):

Leftists have been waging a war against nearly every personal advantage for years: if they aren’t upset because your parents are rich, they’ll insult you because your parents are white, or maybe because you have a penis.  In their most unreasonable moments, they might even be upset that you deserve your own job.  It seems only reasonable to expect that sooner or later, they would be complaining about whether or not our bosses keep themselves in shape.

This is because at the heart of all leftism lies an unreasonable envy of all advantage (disguised as an advocacy of the disadvantaged) and an unhealthy hatred of actual diversity (disguised as an appreciation of difference).  They call life a meritocracy when your successful parents raise you to win, which is a lot like complaining that your parents raised you at all.  It’s almost enough to make you wonder whether they loathe the laws of cause and effect.  In the fight against all odds – not his, but everyone’s – the leftist hasn’t only forgotten that different people breed different people; he’s forgotten that different people are diversity itself, and that diversity, the thing he claims to be championing, means that someone is going to have natural advantages.

Spot on. I have addressed the left’s war on “lookism” in “How to Combat Beauty-ism” and “An Economist’s Special Pleading: Affirmative Action for the Ugly.”

*     *     *

John Ray tackles “Conservative and Liberal Brains Again” (A Western Heart, February 14, 2015):

Most such reports [Current Biology 21, 677–680, April 26, 2011 ª2011. DOI 10.1016/j.cub.2011.03.017] are … parsimoniously interpreted as conservatives being more cautious, which is hardly a discovery. And if there is something wrong with caution then there is everything wrong with a lot of things.  Science, for instance, is a sustained exercise in caution. So conservatives are born more cautious and Leftist brains miss most of that out.  So [a commentary that conservatives are] “sensitive to fear” … could be equally well restated as “cautious”.  And the finding that liberals “have a higher capacity to tolerate uncertainty and conflicts” is pure guesswork [on the part of the commentators].  As the report authors note, that is just “one of the functions of the anterior cingulate cortex”.

Despite the apparent even-handedness of the authors of the study cited by Dr. Ray, the field of psychology has long had a pro-left tilt. See, for example, my posts “Conservatism, Libertarianism, and the ‘Authoritarian Personality’,” “The F Scale, Revisited,” and “The Psychologist Who Played God.”

*     *     *

Income inequality is another item in the long list of subjects about which leftists obsess, despite the facts of the matter. Mark J. Perry, as usual, deals in facts: “US Middle Class Has Disappeared into Higher-Income Groups; Recent Stagnation Explained by Changing Household Demographics?” (, February 4, 2015) and “Evidence Shows That Affluence in the US Is Much More Fluid and Widespread Than The Rigid Class Structure Narrative Suggests” (, February 25, 2015). The only problem with these two posts is Perry’s unnecessary inclusion of a question mark in the title of the first one. For more on the subject, plus long lists of related posts and readings, see my post, “Mass (Economic) Hysteria: Income Inequality and Related Themes.”

*     *     *

Speaking of leftists who obsess about income inequality — and get it wrong — there’s Thomas Piketty, author of the much-rebutted Capital in the Twenty-First Century. I have much to say about Deidre McCloskey’s take-down of Piketty in “McCloskey on Piketty.” David Henderson, whose review of Capital is among the several related readings listed in my post, has more to say; for example:

McCloskey’s review is a masterpiece. She beautifully weaves together economic history, simple price theory, basic moral philosophy, and history of economic thought. Whereas I had mentally put aside an hour to read and think, it took only about 20 minutes. I highly recommend it. (“McCloskey on Piketty,” EconLog, February 25, 2015)

Henderson continues by sampling some of Piketty’s many errors of fact, logic, and economic theory that McCloskey exposes.

*     *     *

Although it won’t matter to committed leftists, Piketty seems to have taken some of this critics to heart. James Pethokoukis writes:

[I]n a new paper, Piketty takes a step or two backward. He now denies that he views his simple economic formula “as the only or even the primary tool for considering changes in income and wealth in the 20th century, or for forecasting the path of income and wealth inequality in the 21st century.” Seems his fundamental law isn’t so fundamental after all once you factor in things like how some of that wealth is (a) spent on super-yachts and bad investments; (b) divided among children through the generations; and (c) already taxed fairly heavily. In particular, the rise in income inequality, as opposed to wealth inequality, has “little to do” with “r > g,” he says….

Piketty’s modest retreat isn’t all that surprising, given the withering academic assault on his research. In a survey of top economists late last year, 81 percent disagreed with his thesis. And several used fairly rough language — at least for scholars — such as “weak” and not “particularly useful,” with one accusing Piketty of “poor theory” and “negligible empirics.”

This is all rather bad news for what I have termed the Unified Economic Theory of Modern Liberalism: Not only are the rich getting richer — and will continue to do so because, you know, capitalism — but this growing gap is hurting economic growth. Redistribution must commence, tout de suite!

But Piketty’s clarification isn’t this politically convenient theory’s only problem. The part about inequality and growth has also suffered a setback. The link between the two is a key part of the “secular stagnation” theory of superstar Democratic economist Lawrence Summers. Since the rich save more than the middle class, growing income inequality is sapping the economy of consumer demand. So government must tax more and spend more. But Summers recently offered an updated view, saying that while boosting consumer demand is necessary, it is not sufficient for strong economic growth. Washington must also do the sort of “supply-side” stuff that Republicans kvetch about, such as business tax reform.

…[C]oncern about the income gap shouldn’t be used an excuse to ignore America’s real top problem, a possible permanent downshift in the growth potential of the U.S. economy. At least Piketty got half his equation right. [“The Politically Convenient but Largely Bogus Unified Economic Theory of Modern Liberalism,” The Week, March 11, 2015]

About that bogus inequality-hurts-growth meme, see my post, “Income Inequality and Economic Growth.”

*     *     *

Harvard’s Robert Putnam is another class warrior, whose propagandistic effusion “E Pluribus Unum: Diversity and Community in the Twenty-first Century“ I skewer in “Society and the State” and “Genetic Kinship and Society.” I was therefore gratified to read in Henry Harpending’s post, “Charles Murray and Robert Putnam on Class” (West Hunter, March 20, 2015) some things said by John Derbyshire about Putnam’s paper:

That paper has a very curious structure. After a brief introduction (two pages), there are three main sections, headed as follows:

The Prospects and Benefits of Immigration and Ethnic Diversity (three pages)
Immigration and Diversity Foster Social Isolation (nineteen pages)
Becoming Comfortable with Diversity (seven pages)

I’ve had some mild amusement here at my desk trying to think up imaginary research papers similarly structured. One for publication in a health journal, perhaps, with three sections titled:

Health benefits of drinking green tea
Green tea causes intestinal cancer
Making the switch to green tea

Social science research in our universities cries out for a modern Jonathan Swift to lampoon its absurdities.


*     *     *

Putnam is a big booster of “diversity,” which — in the left’s interpretation — doesn’t mean diversity of political, social, and economic views. What it means is the forced association of persons of irreconcilably opposed social norms. I say some things about that in “Society and the State” and “Genetic Kinship and Society.” Fred Reed has much more to say in a recent column:

In Ferguson blacks are shooting policemen as others cheer. It does a curmudgeon’s soul good: Everything gets worse, the collapse continues, and unreasoning stupidity goes thundering into the future.

We will hear I suppose that it wasn’t racial, that teens did it, that discrimination  caused it, white privilege, racism, institutional racism, slavery, colonialism, bigots, Southerners, rednecks—everything but the hatred of blacks for whites.

And thus we will avoid the unavoidable, that racial relations are a disaster, will remain a disaster, will get worse, are getting worse, and will lead to some awful denouement no matter how much we lie, preen, vituperate, chatter like Barbary apes, or admire ourselves.

It isn’t working. There is no sign that it ever will. What now?

The only solution, if there is a solution, would seem to be an amicable separation. This methinks would be greatly better than the slow-motion, intensifying racial war we now see, and pretend not to see. When the races mix, there is trouble. So, don’t mix them….

The racial hostility of blacks for whites can be seen elsewhere, for example in targeting of crime, most starkly in interracial rates of rape…. The numbers on rape, almost entirely black on white, also check out as cold fact… This has been analyzed to death, and ignored to death, but perhaps the most readable account is Jim Goad’s For Whom the Cat Calls (the numbers of note come below the ads).

Even without the (inevitable) racial hostility, togetherheid would not work well. The races have little or nothing in common. They do not want the same things. Whites come from a literate European tradition dating at least from the Iliad in 800 BC, a tradition characterized by literature, mathematics, architecture, philosophy, and the sciences. Africa, having a very different social traditions, was barely touched by this, and today blacks still show little interest. Even in the degenerate America of today, whites put far more emphasis on education than do blacks.

The media paint the problems of blacks as consequent to discrimination, but they clearly are not. If blacks in white schools wanted to do the work, or could, whites would applaud. If in black schools they demanded thicker textbooks with bigger words and smaller pictures, no white would refuse. The illiteracy, the very high rates of illegitimacy, the crime in general, the constant killing of young black men by young black men in particular—whites do not do these. They are either genetic, and irremediable, or cultural, and remediable, if at all, only in the very long run. We live in the short run.

Would it then not be reasonable to encourage a voluntary segregation? Having only black policemen in black regions would slow the burning of cities. If we let people live among their own, let them study what they chose to study, let them police themselves and order their schools as they chose, considerable calm would fall over the country.

If the races had the choice of running their own lives apart, they would. If this is not true, why do we have to spend such effort trying to force them together?

It is a great fallacy to think that because we ought to love one another, we will; or that because bloodshed among groups makes no sense, it won’t happen. The disparate seldom get along, whether Tamils and Sinhalese or Hindus and Moslems or Protestants and Catholics or Jews and Palestinians. The greater the cultural and genetic difference, the greater the likelihood and intensity of conflict. Blacks and whites are very, very different….

Separation does not imply disadvantage. The assertion that “separate is inherently unequal” is a catchiphrastic embodiment of the Supreme Court’s characteristic blowing in the political wind. A college for girls is not inherently inferior to a college for boys, nor a yeshiva for Jews inherently inferior to a parish school for Catholics. And maybe it is the business of girls and boys, Catholics and Jews, to decide what and where they want to study—not the government’s business….

Anger hangs over the country. Not everyone white is a professor or collegiate sophomore or network anchor. Not every white—not by a long shot—in Congress or the federal bureaucracy is a Mother Jones liberal, not in private conversation. They say aloud what they have to say. But in the Great Plains and small-town South, in corner bars in Chicago and Denver, in the black enclaves of the cities, a lot of people are ready to rumble. Read the comments section of the St. Louis papers after the riots. We can call the commenters whatever names we choose but when we finish, they will still be there. The shooting of policemen for racial reasons–at least four to date–is not a good sign. We will do nothing about it but chatter. [“The Symptoms Worsen,” Fred on Everything, March 15, 2015]

See also Reed’s column “Diversity: Koom. Bah. Humbug” (January 13, 2015) and my posts, “Race and Reason: The Achievement Gap — Causes and Implications,” “The Hidden Tragedy of the Assassination of Lincoln.”, “‘Conversing’ about Race,” “‘Wading’ into Race, Culture, and IQ,” “Round Up the Usual Suspects,”and “Evolution, Culture, and ‘Diversity’.”

*     *     *

In “The Fallacy of Human Progress” I address at length the thesis of Steven Pinker’s ludicrous The Better Angels of Our Nature: Why Violence Has Declined. In rebuttal to Pinker, I cite John Gray, author of The Silence of Animals: On Progress and Other Modern Myths:

Gray’s book — published  18 months after Better Angels — could be read as a refutation of Pinker’s book, though Gray doesn’t mention Pinker or his book.

Well, Gray recently published a refutation of Pinker’s book, which I can’t resist quoting at length:

The Better Angels of Our Nature: a history of violence and humanity (2011) has not only been an international bestseller – more than a thousand pages long and containing a formidable array of graphs and statistics, the book has established something akin to a contemporary orthodoxy. It is now not uncommon to find it stated, as though it were a matter of fact, that human beings are becoming less violent and more altruistic. Ranging freely from human pre-history to the present day, Pinker presents his case with voluminous erudition. Part of his argument consists in showing that the past was more violent than we tend to imagine…. This “civilising process” – a term Pinker borrows from the sociologist Norbert Elias – has come about largely as a result of the increasing power of the state, which in the most advanced countries has secured a near-monopoly of force. Other causes of the decline in violence include the invention of printing, the empowerment of women, enhanced powers of reasoning and expanding capacities for empathy in modern populations, and the growing influence of Enlightenment ideals….

Another proponent of the Long Peace is the well-known utilitarian philosopher Peter Singer, who has praised The Better Angels of Our Nature as “a supremely important book … a masterly achievement. Pinker convincingly demonstrates that there has been a dramatic decline in violence, and he is persuasive about the causes of that decline.” In a forthcoming book, The Most Good You Can Do, Singer describes altruism as “an emerging movement” with the potential to fundamentally alter the way humans live….

Among the causes of the outbreak of altruism, Pinker and Singer attach particular importance to the ascendancy of Enlightenment thinking….

…Pinker’s response when confronted with [contrary] evidence is to define the dark side of the Enlightenment out of existence. How could a philosophy of reason and toleration be implicated in mass murder? The cause can only be the sinister influence of counter-Enlightenment ideas….

The picture of declining violence presented by this new orthodoxy is not all it seems to be. As some critics, notably John Arquilla, have pointed out, it’s a mistake to focus too heavily on declining fatalities on the battlefield….

If great powers have avoided direct armed conflict, they have fought one another in many proxy wars. Neocolonial warfare in south-east Asia, the Korean war and the Chinese invasion of Tibet, British counter-insurgency warfare in Malaya and Kenya, the abortive Franco-British invasion of Suez, the Angolan civil war, the Soviet invasions of Hungary, Czechoslovakia and Afghanistan, the Vietnam war, the Iran-Iraq war, the first Gulf war, covert intervention in the Balkans and the Caucasus, the invasion of Iraq, the use of airpower in Libya, military aid to insurgents in Syria, Russian cyber-attacks in the Baltic states and the proxy war between the US and Russia that is being waged in Ukraine – these are only some of the contexts in which great powers have been involved in continuous warfare against each other while avoiding direct military conflict.

While it is true that war has changed, it has not become less destructive. Rather than a contest between well-organised states that can at some point negotiate peace, it is now more often a many-sided conflict in fractured or collapsed states that no one has the power to end….

It may be true that the modern state’s monopoly of force has led, in some contexts, to declining rates of violent death. But it is also true that the power of the modern state has been used for purposes of mass killing, and one should not pass too quickly over victims of state terror…. Pinker goes so far as to suggest that the 20th-century Hemoclysm might have been a gigantic statistical fluke, and cautions that any history of the last century that represents it as having been especially violent may be “apt to exaggerate the narrative coherence of this history” (the italics are Pinker’s). However, there is an equal or greater risk in abandoning a coherent and truthful narrative of the violence of the last century for the sake of a spurious quantitative precision….

While the seeming exactitude of statistics may be compelling, much of the human cost of war is incalculable…. [T]he statistics presented by those who celebrate the arrival of the Long Peace are morally dubious if not meaningless.

The radically contingent nature of the figures is another reason for not taking them too seriously. (For a critique of Pinker’s statistical methods, see Nassim Nicholas Taleb’s essay on the Long Peace.)…

Certainly the figures used by Pinker and others are murky, leaving a vast range of casualties of violence unaccounted for. But the value of these numbers for such thinkers comes from their very opacity. Like the obsidian mirrors made by the Aztecs for purposes of divination, these rows of graphs and numbers contain nebulous images of the future – visions that by their very indistinctness can give comfort to believers in human improvement….

Unable to tolerate the prospect that the cycles of conflict will continue, many are anxious to find continuing improvement in the human lot. Who can fail to sympathise with them? Lacking any deeper faith and incapable of living with doubt, it is only natural that believers in reason should turn to the sorcery of numbers. How else can they find meaning in their lives? [“John Gray: Steven Pinker Is Wrong about Violence and War,” The Guardian, March 13, 2015]

 *     *     *

I close this super-sized installment of “Thoughts” by returning to the subject of so-called net neutrality, which I addressed almost nine years ago in “Why ‘Net Neutrality’ Is a Bad Idea.” Now it’s a bad idea that the FCC has imposed on ISPs and their customers — until, one hopes, it’s rejected by the Supreme Court as yet another case of Obamanomic overreach.

As Robert Tracinski notes,

[b]illionaire investor Mark Cuban recently commented, about a push for new regulations on the Internet, that “In my adult life I have never seen a situation that paralleled what I read in Ayn Rand’s books until now with Net Neutrality.” He continued, “If Ayn Rand were an up-and-coming author today, she wouldn’t write about steel or railroads, it would be Net Neutrality.”

She certainly would, but if he thinks this is the first time real life has imitated Ayn Rand’s fiction, he needs to be paying a little more attention. Atlas has been shrugging for a long, long time. [“Net Neutrality: Yes, Mark Cuban, Atlas Is Shrugging,” The Federalist, March 18, 2015]

The rest of the story is outlined by the headings in Tracinski’s article:

The Relationship Between Net Neutrality and Atlas Shrugged

Internet Execs Are Already Uncomfortable with the Net Neutrality They Demanded

The Parallels Extend Into Fracking

Government Shuts Down Any Runaway Success

Atlas Shrugged Is Coming True Before Our Eyes

As I did in my post, Julian Adorney focuses on the economics of net neutrality:

After a number of false starts and under pressure from the White House, the FCC gave in and voted to regulate the Internet as a public utility in order to ban such practices, thus saving the Internet from a variety of boogeymen.

This is a tempting narrative. It has conflict, villains, heroes, and even a happy ending. There’s only one problem: it’s a fairy tale. Such mischief has been legal for decades, and ISPs have almost never behaved this way. Any ISP that created “slow lanes” or blocked content to consumers would be hurting its own bottom line. ISPs make money by seeking to satisfy consumers, not by antagonizing them.

There are two reasons that ISPs have to work to satisfy their customers. First, every company needs repeat business….

For Internet service providers, getting new business is expensive…. Satisfying customers so that they continue subscribing is cheaper, easier, and more profitable than continually replacing them. ISPs’ self-interest pushes them to add value to their customers just to keep them from jumping ship to their competitors.

In fact, this is what we’ve seen. ISPs have invested heavily in new infrastructure, and Internet speeds have increased by leaps and bounds…. These faster speeds have not been limited to big corporate customers: ISPs have routinely improved their services to regular consumers. They didn’t do so because the FCC forced them. For the past twenty years, “slow lanes” have been perfectly legal and almost as perfectly imaginary….

…ISPs shy away from creating slow lanes not because they have to but because they have a vested interest in offering fast service to all customers.

Contrary to the myth about ISPs being localized monopolies, 80 percent of Americans live in markets with access to multiple high-speed ISPs. While expensive regulations can discourage new players from entering the market, competition in most cities is increasingly robust….

ISPs still have to compete with each other for customers. If one ISP sticks them in the slow lane or blocks access to certain sites — or even just refuses to upgrade its service — consumers can simply switch to a competitor.

The second reason that ISPs seek to satisfy customers is that every business wants positive word of mouth. Consumers who receive excellent service talk up the service to their friends, generating new sign-ups. Consumers who receive mediocre service not only leave but badmouth the company to everyone they know.

In fact, this happened in one of the few cases where an ISP chose to discriminate against content. When Verizon blocked text messages from a pro-choice activist group in 2007, claiming the right to block “controversial or unsavory” messages, the backlash was fierce. Consumer Affairs notes that, “after a flurry of criticism, Verizon reversed its policy” on the pro-choice texts. The decision may have been ideological, but more likely Verizon reversed a policy that was driving away consumers, generating bad press, and hurting its bottom line.

In 2010, an FCC order made such “unreasonable discrimination” illegal (until the rule was struck down in 2014), but even without this rule, consumers proved more than capable of standing up to big corporations and handling such discrimination themselves.

In competitive markets, the consumer’s demand for quality prevents companies from cutting corners. Before the FCC imposed public utility regulations on the Internet, ISPs were improving service and abandoning discriminatory practices in order to satisfy their users. Net Neutrality advocates have spent years demanding a government solution to a problem that  markets had already solved. [“Net Nonsense,” The Freeman, March 18, 2015]

Amen, again.

Not-So-Random Thoughts (XII)

Links to the other posts in this occasional series may be found at “Favorite Posts,” just below the list of topics.

*     *     *

Intolerance as Illiberalism” by Kim R. Holmes (The Public Discourse, June 18, 2014) is yet another reminder, of innumerable reminders, that modern “liberalism” is a most intolerant creed. See my ironically titled “Tolerance on the Left” and its many links.

*     *     *

Speaking of intolerance, it’s hard to top a strident atheist like Richard Dawkins. See John Gray’s “The Closed Mind of Richard Dawkins” (The New Republic, October 2, 2014). Among the several posts in which I challenge the facile atheism of Dawkins and his ilk are “Further Thoughts about Metaphysical Cosmology” and “Scientism, Evolution, and the Meaning of Life.”

*     *     *

Some atheists — Dawkins among them — find a justification for their non-belief in evolution. On that topic, Gertrude Himmelfarb writes:

The fallacy in the ethics of evolution is the equation of the “struggle for existence” with the “survival of the fittest,” and the assumption that “the fittest” is identical with “the best.” But that struggle may favor the worst rather than the best. [“Evolution and Ethics, Revisited,” The New Atlantis, Spring 2014]

As I say in “Some Thoughts about Evolution,”

Survival and reproduction depend on many traits. A particular trait, considered in isolation, may seem to be helpful to the survival and reproduction of a group. But that trait may not be among the particular collection of traits that is most conducive to the group’s survival and reproduction. If that is the case, the trait will become less prevalent. Alternatively, if the trait is an essential member of the collection that is conducive to survival and reproduction, it will survive. But its survival depends on the other traits. The fact that X is a “good trait” does not, in itself, ensure the proliferation of X. And X will become less prevalent if other traits become more important to survival and reproduction.

The same goes for “bad” traits. Evolution is no guarantor of ethical goodness.

*     *     *

It shouldn’t be necessary to remind anyone that men and women are different. But it is. Lewis Wolpert gives it another try in “Yes, It’s Official, Men Are from Mars and Women from Venus, and Here’s the Science to Prove It” (The Telegraph, September 14, 2014). One of my posts on the subject is “The Harmful Myth of Inherent Equality.” I’m talking about general tendencies, of course, not iron-clad rules about “men’s roles” and “women’s roles.” Aside from procreation, I can’t readily name “roles” that fall exclusively to men or women out of biological necessity. There’s no biological reason, for example, that an especially strong and agile woman can’t be a combat soldier. But it is folly to lower the bar just so that more women can qualify as combat soldiers. The same goes for intellectual occupations. Women shouldn’t be discouraged from pursuing graduate degrees and professional careers in math, engineering, and the hard sciences, but the qualifications for entry and advancement in those fields shouldn’t be watered down just for the sake of increasing the representation of women.

*     *     *

Edward Feser, writing in “Nudge Nudge, Wink Wink” at his eponymous blog (October 24, 2014), notes

[Michael] Levin’s claim … that liberal policies cannot, given our cultural circumstances, be neutral concerning homosexuality.  They will inevitably “send a message” of approval rather than mere neutrality or indifference.

Feser then quotes Levin:

[L]egislation “legalizing homosexuality” cannot be neutral because passing it would have an inexpungeable speech-act dimension.  Society cannot grant unaccustomed rights and privileges to homosexuals while remaining neutral about the value of homosexuality.

Levin, who wrote that 30 years ago, gets a 10 out 10 for prescience. Just read “Abortion, ‘Gay Rights’, and Liberty” for a taste of the illiberalism that accompanies “liberal” causes like same-sex “marriage.”

*     *     *

“Liberalism” has evolved into hard-leftism. It’s main adherents are now an elite upper crust and their clients among the hoi polloi. Steve Sailer writes incisively about the socioeconomic divide in “A New Caste Society” (Taki’s Magazine, October 8, 2014). “‘Wading’ into Race, Culture, and IQ” offers a collection of links to related posts and articles.

*     *     *

One of the upper crust’s recent initiatives is so-called libertarian paternalism. Steven Teles skewers it thoroughly in “Nudge or Shove?” (The American Interest, December 10, 2014), a review of Cass Sunstein’s Why Nudge? The Politics of Libertarian Paternalism. I have written numerous times about Sunstein and (faux) libertarian paternalism. The most recent entry, “The Sunstein Effect Is Alive and  Well in the White House,” ends with links to two dozen related posts. (See also Don Boudreaux, “Where Nudging Leads,” Cafe Hayek, January 24, 2015.)

*     *     *

Maria Konnikova gives some space to Jonathan Haidt in “Is Social Psychology Biased against Republicans?” (The New Yorker, October 30, 2014). It’s no secret that most academic disciplines other than math and the hard sciences are biased against Republicans, conservatives, libertarians, free markets, and liberty. I have something to say about it in “The Pseudo-Libertarian Temperament,” and in several of the posts listed here.

*     *     *

Keith E. Stanovich makes some good points about the limitations of intelligence in “Rational and Irrational Thought: The Thinking that IQ Tests Miss” (Scientific American, January 1, 2015). Stanovich writes:

The idea that IQ tests do not measure all the key human faculties is not new; critics of intelligence tests have been making that point for years. Robert J. Sternberg of Cornell University and Howard Gardner of Harvard talk about practical intelligence, creative intelligence, interpersonal intelligence, bodily-kinesthetic intelligence, and the like. Yet appending the word “intelligence” to all these other mental, physical and social entities promotes the very assumption the critics want to attack. If you inflate the concept of intelligence, you will inflate its close associates as well. And after 100 years of testing, it is a simple historical fact that the closest associate of the term “intelligence” is “the IQ test part of intelligence.”

I make a similar point in “Intelligence as a Dirty Word,” though I don’t denigrate IQ, which is a rather reliable predictor of performance in a broad range of endeavors.

*     *     *

Brian Caplan, whose pseudo-libertarianism rankles, tries to defend the concept of altruism in “The Evidence of Altruism” (EconLog, December 30, 2014). Caplan aids his case by using the loaded “selfishness” where he means “self-interest.” He also ignores empathy, which is a key ingredient of the Golden Rule. As for my view of altruism (as a concept), see “Egoism and Altruism.”

Some Thoughts about Probability


This post is prompted by a reader’s comments about “The Compleat Monty Hall Problem.” I open with a discussion of probability and its inapplicability to single games of chance (e.g., one toss of a coin). With that as background, I then address the reader’s specific comments. I close with a discussion of the debasement of the meaning of probability.


What is probability? Is it a property of a thing (e.g., a coin), a property of an event involving a thing (e.g., a toss of the coin), or a description of the average outcome of a large number of such events (e.g., “heads” and “tails” will come up about the same number of times)? I take the third view.

What does it mean to say, for example, that there’s a probability of 0.5 (50 percent) that a tossed coin will come up “heads” (H), and a probability of 0.5 that it will come up “tails” (T)? Does such a statement have any bearing on the outcome of a single toss of a coin? No, it doesn’t. The statement is only a short way of saying that in a sufficiently large number of tosses, approximately half will come up H and half will come up T. The result of each toss, however, is a random event — it has no probability.

That is the standard, frequentist interpretation of probability, to which I subscribe. It replaced the classical interpretation , which is problematic:

If a random experiment can result in N mutually exclusive and equally likely outcomes and if NA of these outcomes result in the occurrence of the event A, the probability of A is defined by

P(A) = {N_A \over N} .

There are two clear limitations to the classical definition.[16] Firstly, it is applicable only to situations in which there is only a ‘finite’ number of possible outcomes. But some important random experiments, such as tossing a coin until it rises heads, give rise to an infinite set of outcomes. And secondly, you need to determine in advance that all the possible outcomes are equally likely without relying on the notion of probability to avoid circularity….

A similar charge has been laid against frequentism:

It is of course impossible to actually perform an infinity of repetitions of a random experiment to determine the probability of an event. But if only a finite number of repetitions of the process are performed, different relative frequencies will appear in different series of trials. If these relative frequencies are to define the probability, the probability will be slightly different every time it is measured. But the real probability should be the same every time. If we acknowledge the fact that we only can measure a probability with some error of measurement attached, we still get into problems as the error of measurement can only be expressed as a probability, the very concept we are trying to define. This renders even the frequency definition circular.

Not so:

  • There is no “real probability.” If there were, the classical theory would measure it, but the classical theory is circular, as explained above.
  • It is therefore meaningless to refer to “error of measurement.” Estimates of probability may well vary from one series of trials to another. But they will “tend to a fixed limit” over many trials (see below).

There are other approaches to probability. See, for example, this, this, and this.) One approach is known as propensity probability:

Propensities are not relative frequencies, but purported causes of the observed stable relative frequencies. Propensities are invoked to explain why repeating a certain kind of experiment will generate a given outcome type at a persistent rate. A central aspect of this explanation is the law of large numbers. This law, which is a consequence of the axioms of probability, says that if (for example) a coin is tossed repeatedly many times, in such a way that its probability of landing heads is the same on each toss, and the outcomes are probabilistically independent, then the relative frequency of heads will (with high probability) be close to the probability of heads on each single toss. This law suggests that stable long-run frequencies are a manifestation of invariant single-case probabilities.

This is circular. You observe the relative frequencies of outcomes and, lo and behold, you have found the “propensity” that yields those relative frequencies.

Another approach is Bayesian probability:

Bayesian probability represents a level of certainty relating to a potential outcome or idea. This is in contrast to a frequentist probability that represents the frequency with which a particular outcome will occur over any number of trials.

An event with Bayesian probability of .6 (or 60%) should be interpreted as stating “With confidence 60%, this event contains the true outcome”, whereas a frequentist interpretation would view it as stating “Over 100 trials, we should observe event X approximately 60 times.”

Or consider this account:

The Bayesian approach to learning is based on the subjective interpretation of probability.   The value of the proportion p is unknown, and a person expresses his or her opinion about the uncertainty in the proportion by means of a probability distribution placed on a set of possible values of p….

“Level of certainty” and “subjective interpretation” mean “guess.” The guess may be “educated.” It’s well known, for example, that a balanced coin will come up heads about half the time, in the long run. But to say that “I’m 50-percent confident that the coin will come up heads” is to say nothing meaningful about the outcome of a single coin toss. There are as many probable outcomes of a coin toss as there are bystanders who are willing to make a statement like “I’m x-percent confident that the coin will come up heads.” Which means that a single toss doesn’t have a probability, though it can be the subject of many opinions as to the outcome.

Returning to reality, Richard von Mises eloquently explains frequentism in Probability, Statistics and Truth (second revised English edition, 1957). Here are some excerpts:

The rational concept of probability, which is the only basis of probability calculus, applies only to problems in which either the same event repeats itself again and again, or a great number of uniform elements are involved at the same time. Using the language of physics, we may say that in order to apply the theory of probability we must have a practically unlimited sequence of uniform observations. [P. 11]

*     *     *

In games of dice, the individual event is a single throw of the dice from the box and the attribute is the observation of the number of points shown by the dice. In the game of “heads or tails”, each toss of the coin is an individual event, and the side of the coin which is uppermost is the attribute. [P. 11]

*     *     *

We must now introduce a new term…. This term is “the collective”, and it denotes a sequence of uniform events or processes which differ by certain observable attributes…. All the throws of dice made in the course of a game [of many throws] from a collective wherein the attribute of the single event is the number of points thrown…. The definition of probability which we shall give is concerned with ‘the probability of encountering a single attribute in a given collective’. [Pp. 11-12]

*     *     *

[A] collective is a mass phenomenon or a repetitive event, or, simply, a long sequence of observations for which there are sufficient reasons to believe that the relative frequency of the observed attribute would tend to a fixed limit if the observations were indefinitely continued. The limit will be called the probability of the attribute considered within the collective. [P. 15, emphasis in the original]

*     *     *

The result of each calculation … is always … nothing else but a probability, or, using our general definition, the relative frequency of a certain event in a sufficiently long (theoretically, infinitely long) sequence of observations. The theory of probability can never lead to a definite statement concerning a single event. The only question that it can answer is: what is to be expected in the course of a very long sequence of observations? [P. 33, emphasis added]

As stated earlier, it is simply meaningless to say that the probability of H or T coming up in a single toss is 0.5. Here’s the proper way of putting it: There is no reason to expect a single coin toss to have a particular outcome (H or T), given that the coin is balanced, the toss isn’t made is such a way as to favor H or T, and there are no other factors that might push the outcome toward H or T. But to say that P(H) is 0.5 for a single toss is to misrepresent the meaning of probability, and to assert something meaningless about a single toss.

If you believe that probabilities attach to a single event, you must also believe that a single event has an expected value. Let’s say, for example, that you’re invited to toss a coin once, for money. You get $1 if H comes up; you pay $1 if T comes up. As a believer in single-event probabilities, you “know” that you have a “50-50 chance” of winning or losing. Would you play a single game, which has an expected value of $0? If you would, it wouldn’t be because of the expected value of the game; it would be because you might win $1, and because losing $1 would mean little to you.

Now, change the bet from $1 to $1,000. The “expected value” of the single game remains the same: $0. But the size of the stake wonderfully concentrates your mind. You suddenly see through the “expected value” of the game. You are struck by the unavoidable fact that what really matters is the prospect of winning $1,000 or losing $1,000, because those are the only possible outcomes.

Your decision about playing a single game for $1,000 will depend on your finances (e.g., you may be very wealthy or very desperate for money) and your tolerance for risk (e.g., you may be averse to risk-taking or addicted to it). But — if you are rational — you will not make your decision on the basis of the fictional expected value of a single game, which derives from the fictional single-game probabilities of H and T. You will decide whether you’re willing and able to risk the loss of $1,000.

Do I mean to say that probability is irrelevant to a single play of the Monty Hall problem, or to a choice between games of chance? If you’re a proponent of propensity, you might say that in the Monty Hall game the prize has a propensity to be behind the other unopened door (i.e., the door not chosen by you and not opened by the host). But does that tell you anything about the actual location of the prize in a particular game? No, because the “propensity” merely reflects the outcomes of many games; it says nothing about a single game, which (like Schrödinger’s cat) can have only a single outcome (prize or no prize), not 2/3 of one.

If you’re a proponent of Bayesian probability, you might say that you’re confident with “probability” 2/3 that the prize is behind the other unopened door. But that’s just another way of saying that contestants win 2/3 of the time if they always switch doors. That’s the background knowledge that you bring to your statement of confidence. But someone who’s ignorant of the Monty Hall problem might be confident with 1/2 “probability” that the prize is behind the other unopened door. And he could be right about a particular game, despite his lower level of confidence.

So, yes, I do mean to say that there’s no such thing as a single-case probability. You may have an opinion ( or a hunch or a guess) about the outcome of a single game, but it’s only your opinion (hunch, guess). In the end, you have to bet on a discrete outcome. If it gives you comfort to switch to the unopened door because that’s the winning door 2/3 of the time (according to classical probability) and about 2/3 of the time (according to the frequentist interpretation), be my guest. I might do the same thing, for the same reason: to be comfortable about my guess. But I’d be able separate my psychological need for comfort from the reality of the situation:

A single game is just one event in the long series of events from which probabilities emerge. I can win the Monty Hall game about 2/3 of the time in repeated plays if I always switch doors. But that probability has nothing to do with a single game, the outcome of which is a random occurrence.


I now turn to the reader’s specific comments, which refer to “The Compleat Monty Hall Problem.” (You should read it before continuing with this post if you’re unfamiliar with the Monty Hall problem or my analysis of it.) The reader’s comments — which I’ve rearranged slightly — are in italic type. (Here and there, I’ve elaborated on the reader’s comments; my elaborations are placed in brackets and set in roman type.) My replies are in bold type.

I find puzzling your statement that a probability cannot “describe” a single instance, eg one round of the Monty Hall problem.

See my introductory remarks.

While the long run result serves to prove the probability of a particular outcome, that does not mean that that probability may not be assigned to a smaller number of instances. That is the beauty of probability.

The long-run result doesn’t “prove” the probability of a particular outcome; it determines the relative frequency of occurrence of that outcome — and nothing more. There is no probability associated with a “smaller number of instances,” certainly not 1 instance. Again, see my introductory remarks.

If the [Monty Hall] game is played once [and I don’t switch doors], I should budget for one car [the prize that’s usually cited in discussions of the Monty hall problem], and if it is played 100 times [and I never switch doors], I budget for 33….

“Budget” seems to refer to the expected number of cars won, given the number of plays of the game and a strategy of never switching doors. The reader contradicts himself by “budgeting” for 1 car in a single play of the Monty Hall problem. In doing so, he is being unfaithful to his earlier statement: “While the long run result serves to prove the probability of a particular outcome, that does not mean that that probability may not be assigned to a smaller number of instances.” Removing the double negatives, we get “probability may be assigned to a smaller number of instances.” Given that 1 is a smaller number than 100, it follows, by the reader’s logic, that his “budget” for a single game should be 1/3 car (assuming, as he does, a strategy of not switching doors). The reader’s problem here is his insistence that a probability expresses something other than the long-run relative frequency of a particular outcome.

To justify your contrary view, you ask how you can win 2/3 of a car [the long-run average if the contestant plays many games and always switches doors]; you can win or you can not win, you say, you cannot partly win. Is this not sophistry or a straw man, sloppy reasoning at best, to convince uncritical thinkers who agree that you cannot drive 2/3 of a car?

My “contrary view” of what? My view of statistics isn’t “contrary.” Rather, it’s in line with the standard, frequentist interpretation.

It’s a simple statement of obvious fact you can’t win 2/3 of a car. There’s no “sophistry” or “straw man” about it. If you can’t win 2/3 of a car, what does it mean to assign a probability of 2/3 to winning a car by adopting the switching strategy? As discussed above, it means only one thing: A long series of games will be won about 2/3 of the time if all contestants adopt the switching strategy.

On what basis other than an understanding of probability would you be optimistic at the prospect of being offered one chance of picking a single Golden Ball worth $1m from a bag of just three balls and pessimistic about your prospects of picking the sole Golden Ball from a barrel of 10,000 balls?

The only difference between the two games is that on the one hand you have a decent (33%) chance of winning and on the other hand you have a lousy (0.01%) chance. Isn’t it these disparate probabilities that give you cause for optimism or pessimism, as the case may be?

“Optimism” and “pessimism” — like “comfort” — are subjective terms for ill-defined states of mind. There are persons who will be “optimistic” about a given situation, and persons who will be “pessimistic” about the same situation. For example: There are hundreds of millions of persons who are “optimistic” about winning various lotteries, even though they know that the grand prize in each lottery will be assigned to only one of millions of possible numbers. By the same token, there are hundreds of millions of persons who, knowing the same facts, refuse to buy lottery tickets because they are “pessimistic” about the likely outcome of doing so. But “optimism” and “pessimism” — like “comfort” — have nothing to do with probability, which isn’t an attribute of a single game.

If probability cannot describe the chances of each of the two one-off “games”, does that mean I could not provide a mathematical basis for my advice that you play the game with 3 balls (because you have a one-in-three chance of winning) rather than the ball in the barrel game which offers a one in ten thousand chance of winning?

You can provide a mathematical basis for preferring the game with 3 balls. But you must, in honesty, state that the mathematical basis applies only to many games, and that the outcome of a single game is unpredictable.

It might be that probability cannot reliably describe the actual outcome of a single event because the sample size of 1 game is too small to reflect the long-run average that proves the probability. However, comparing the probabilities for winning the two games describes the relative likelihood of winning each game and informs us as to which game will more likely provide the prize.

If not by comparing the probability of winning each game, how do we know which of the two games has a better chance of delivering a win? One cannot compare the probability of selecting the Golden Ball from each of the two games unless the probability of each game can be expressed, or described, as you say.

Here, the reader comes close to admitting that a probability can’t describe the (expected) outcome of a single event (“reliably” is superfluous). But he goes off course when he says that “comparing the probabilities for the two games … informs us as to which game will more likely provide the prize.” That statement is true only for many plays of the two ball games. It has nothing to do with a single play of either ball game. The choice there must be based on subjective considerations: “optimism,” “pessimism,” “comfort,” a guess, a hunch, etc.

Can I not tell a smoker that their lifetime risk of developing lung cancer is 23% even though smokers either get lung cancer or they do not? No one gets 23% cancer. Did someone say they did? No one has 0.2 of a child either but, on average, every family in a census did at one stage have 2.2 children.

No, the reader may not (honestly) tell a smoker that his lifetime risk of developing lung cancer is 23 percent, or any specific percentage. The smoker has one life to live; he will either get lung cancer or he will not. What the reader may honestly tell the smoker is that statistics based on the fates of a large number of smokers over many decades indicate that a certain percentage of those smokers contracted lung cancer. The reader should also tell the smoker that the frequency of the incidence of lung cancer in a large population varies according to the number of cigarettes smoked daily. (According to Wikipedia: “For every 3–4 million cigarettes smoked, one lung cancer death occurs.[1][132]“) Further, the reader should note that the incidence of lung cancer also varies with the duration of smoking at various rates, and with genetic and environmental factors that vary from person to person.

As for family size, given that the census counts only post-natal children (who come in integer values), how could “every family in a census … at one stage have 2.2 children”? The average number of children across a large number of families may be 2.2, but surely the reader knows that “every family” did not somehow have 2.2 children “at one stage.” And surely the reader knows that average family size isn’t a probabilistic value, one that measures the relative frequency of an event (e.g., “heads”) given many repetitions of the same trial (e.g., tossing a fair coin), under the same conditions (e.g., no wind blowing). Each event is a random occurrence within the long string of repetitions. The reader may have noticed that family size is in fact strongly determined (especially in Western countries) by non-random events (e.g., deliberate decisions by couples to reproduce, or not). In sum, probabilities may represent averages, but not all (or very many) averages represent probabilities.

If not [by comparing probabilities], how do we make a rational recommendation and justify it in terms the board of a think-tank would accept? [This seems to be a reference to my erstwhile position as an officer of a defense think-tank.]

Here, the reader extends an inappropriate single-event view of probability to an inappropriate unique-event view. I would not have gone before the board and recommended a course of action — such as bidding on a contract for a new line of work — based on a “probability of success.” That would be an absurd statement to make about an event that is defined by unique circumstances (e.g., the composition of the think-tank’s staff at that time, the particular kind of work to be done, the qualifications of prospective competitors’ staffs). I would simply have spelled out the facts and the uncertainties. And if I had a hunch about the likely success or failure of the venture, I would have recommended for or against it, giving specific reasons for my hunch (e.g., the relative expertise of our staff and competitors’ staffs). But it would have been nothing more than a hunch; it wouldn’t have been my (impossible) assessment of the probability of a unique event.

Boards (and executives) don’t base decisions on (non-existent) probabilities; they base decisions on unique sets of facts, and on hunches (preferably hunches rooted in knowledge and experience). Those hunches may sometimes be stated as probabilities, as in “We’ve got a 50-50 chance of winning the contract.” (Though I would never say such a thing.) But such statements are only idiomatic, and have nothing to do with probability as it is properly understood.


The reader’s comments reflect the popular debasement of the meaning of probability. The word has been adapted to many inappropriate uses: the probability of precipitation (a quasi-subjective concept), the probability of success in a business venture (a concept that requires the repetition of unrepeatable events), the probability that a batter will get a hit in his next at-bat (ditto, given the many unique conditions that attend every at-bat), and on and on. The effect of all such uses (and, often, the purpose of such uses) is to make a guess seem like a “scientific” prediction.

ADDENDUM (02/09/15)

The reader whose comments about “The Compleat Monty Hall Problem” I address above has submitted some additional comments.

The first additional comment pertains to this exchange where the reader’s remarks are in italics and my reply is in bold:

If the [Monty Hall] game is played once [and I don’t switch doors], I should budget for one car [the prize that’s usually cited in discussions of the Monty hall problem], and if it is played 100 times [and I never switch doors], I budget for 33….

“Budget” seems to refer to the expected number of cars won, given the number of plays of the game and a strategy of never switching doors. The reader contradicts himself by “budgeting” for 1 car in a single play of the Monty Hall problem. In doing so, he is being unfaithful to his earlier statement: “While the long run result serves to prove the probability of a particular outcome, that does not mean that that probability may not be assigned to a smaller number of instances.” Removing the double negatives, we get “probability may be assigned to a smaller number of instances.” Given that 1 is a smaller number than 100, it follows, by the reader’s logic, that his “budget” for a single game should be 1/3 car (assuming, as he does, a strategy of not switching doors). The reader’s problem here is his insistence that a probability expresses something other than the long-run relative frequency of a particular outcome.

The reader’s rejoinder (with light editing by me):

The game-show producer “budgets” one car if playing just one game because losing one car is a possible outcome and a prudent game-show producer would cover all possibilities, the loss of one car being one of them.  This does not contradict anything I have said, it is simply the necessary approach to manage the risk of having a winning contestant and no car.  Similarly, the producer budgets 33 cars for a 100-show season [TEA: For consistency, “show” should be “game”].

The contradiction is between the reader’s use of an expected-value calculation for 100 games, but not for a single game. If the game-show producer knows (how?) that contestants will invariably stay with the doors they’ve chosen initially, a reasonable budget for a 100-game season is 33 cars. (But a “reasonable” budget isn’t a foolproof one, as I show below.) By the same token, a reasonable budget for a single game — a game played only once, not one game in a series — is 1/3 car. After all, that is the probabilistic outcome of a single game if you believe that a probability can be assigned to a single game. And the reader does believe that; here’s the first sentence of his original comments:

I find puzzling your statement that a probability cannot “describe” a single instance, eg one round of the Monty Hall problem. [See the section “Replies to a Reader’s Comments” in “Some Thoughts about Probability.”]

Thus, according the reader’s view of probability, the game-show producer should budget for 1/3 car. After all, in the reader’s view, there’s a 2/3 probability that a contestant won’t win a car in a one-game run of the show.

The reader could respond that cars come in units of one. True, but the designation of a car as the prize is arbitrary (and convenient for the reader). The prize could just as well be money — $30,000 for example. If the contestant wins a car in the (rather contrived) one-game run of the show, the producer then (and only then) gives the contestant a check for $30,000. But, by the reader’s logic, the game has two other equally likely outcomes: the contestant loses and the contestant loses. If those outcomes prevail, the producer doesn’t have to write a check. So, the average prize for the one-game run of the show would be $10,000, or the equivalent of 1/3 car.

Now, the producer might hedge his bets because the outcome of a single game is uncertain; that is, he might budget one car or $30,000. But by the same logic, the producer should budget 100 cars or $3,000,000 for 100 games, not 33 cars or $990,000. Again, the reader contradicts himself. He uses an expected-value calculation for one game but not for 100 games.

What is a “reasonable” budget for 100 games, or fewer than 100 games? Well, it’s really a subjective call that the producer must make, based on his tolerance for risk. The producer who budgets 33 cars or $990,000 for 100 games on the basis of an expected-value calculation may find himself without a job.

Using a random-number generator, I set up a simulation of the outcomes of games 1 through 100, where the contestant always stays with the door originally chosen . Here are the results of the first five simulations that I ran:

Results of 100 games_1

Results of 100 games_2

Results of 100 games_3

Results of 100 games_4

Results of 100 games_5

Some observations:

Outcomes of individual games are unpredictable, as evidenced by the wild swings and jagged lines, the latter of which persist even at 100 games.

Taking the first game as a proxy for a single-game run of the show, we see that the contestant won that game in just one of the five simulations. To put it another way, in four of the five cases the producer would have thrown away his money on a rapidly depreciating asset (a car) if had offered a car as the prize.

Results vary widely and wildly after the first game. At 10 and 20 games, contestants are doing better than expected in four of the five simulations. At 30 games, contestants are doing as well or better than expected in all five simulations. At 100 games, contestants are doing better than expected in two simulation, worse than expected in two simulation, and exactly as expected in one simulation. What should the producer do with such information? Well, it’s up to the producer and his tolerance for risk. But a prudent producer wouldn’t budget 33 cars or $990,000 just because that’s the expected value of 100 games.

It can take a lot of games to yield an outcome that comes close to 1/3 car per game. A game-show producer could easily lose his shirt by “betting” on 1/3 car per game for a season much shorter than 100 games, and even for a season of 100 games.

*     *     *

The reader’s second additional comment pertains to this exchange:

On what basis other than an understanding of probability would you be optimistic at the prospect of being offered one chance of picking a single Golden Ball worth $1m from a bag of just three balls and pessimistic about your prospects of picking the sole Golden Ball from a barrel of 10,000 balls?

The only difference between the two games is that on the one hand you have a decent (33%) chance of winning and on the other hand you have a lousy (0.01%) chance. Isn’t it these disparate probabilities that give you cause for optimism or pessimism, as the case may be?

“Optimism” and “pessimism” — like “comfort” — are subjective terms for ill-defined states of mind. There are persons who will be “optimistic” about a given situation, and persons who will be “pessimistic” about the same situation. For example: There are hundreds of millions of persons who are “optimistic” about winning various lotteries, even though they know that the grand prize in each lottery will be assigned to only one of millions of possible numbers. By the same token, there are hundreds of millions of persons who, knowing the same facts, refuse to buy lottery tickets because they are “pessimistic” about the likely outcome of doing so. But “optimism” and “pessimism” — like “comfort” — have nothing to do with probability, which isn’t an attribute of a single game.

The reader now says this:

Optimism or pessimism are states as much as something being hot or cold, or a person perspiring or not, and one would find a lot more confidence among contestants playing a single instance of a 1-in-3 game than one would find amongst contestants playing a 1-in-1b game.

Apart from differing probabilities, how would you explain the higher levels of confidence among players of the 1-in-3 game?

Alternatively, what about a “game” involving 2 electrical wires, one live and one neutral, and a game involving one billion electrical wires, only one of which is live?  Contestants are offered $1m if they are prepared to touch one wire.  No one accepts the dare in the 1-in-2 game but a reasonable percentage accept the dare in the 1-in-1b game.

Is the probable outcome of a single event a factor in the different rates of uptake between the two games?

The reader begs the question by introducing “hot or cold” and “perspiring or not,” which have nothing to do with objective probabilities (long-run frequencies of occurrence) and everything to do with individual attitudes toward risk-taking. That was the point of my original response, and I stand by it. The reader simply tries to evade the point by reading the minds of his hypothetical contestants (“higher levels of confidence among players of the 1-in-3 game”). He fails to address the basic issue, which is whether or not there are single-case probabilities — an issue that I addressed at length in “Some Thoughts…”.

The alternative hypotheticals involving electrical wires are just variants of the original one. They add nothing to the discussion.

*     *     *

Enough of this. If the reader — or anyone else — has some good arguments to make in favor of single-case probabilities, drop me a line. If your thoughts have merit, I may write about them.


The Harmful Myth of Inherent Equality

Malcolm Gladwell popularized the 10,000-hour rule in Outliers: The Story of Success. According to the Wikipedia article about the book,

…Gladwell repeatedly mentions the “10,000-Hour Rule”, claiming that the key to success in any field is, to a large extent, a matter of practicing a specific task for a total of around 10,000 hours….

…[T]he “10,000-Hour Rule” [is] based on a study by Anders Ericsson. Gladwell claims that greatness requires enormous time, using the source of The Beatles’ musical talents and Gates’ computer savvy as examples….

Reemphasizing his theme, Gladwell continuously reminds the reader that genius is not the only or even the most important thing when determining a person’s success….

For “genius” read “genes.” Gladwell’s borrowed theme reinforces the left’s never-ending effort to sell the idea that all men and women are born with the same potential. And, of course, it’s the task of the almighty state to ensure that outcomes (e.g., housing, jobs, college admissions, and income) conform to nature’s design.

I encountered the 10,000-hour rule several years ago, and referred to it in this post, where I observed that “outcomes are skewed … because talent is distributed unevenly.” By “talent” I mean inherent ability of a particular kind — high intelligence and athletic prowess, for example — the possession of which obviously varies from person to person and (on average) from gender to gender and race to race. Efforts to deny such variations are nothing less than anti-scientific. They exemplify the left’s penchant for magical thinking.

There’s plenty of evidence of the strong link between inherent ability to success in any endeavor. I’ve offered some evidence here, here, here, and here. Now comes “Practice Does Not Make Perfect” by , , and (Slate, September 28, 2014). The piece veers off into social policy (with a leftish tinge) and an anemic attempt to rebut the race-IQ correlation, but it’s good on the facts. First, the authors frame the issue:

…What makes someone rise to the top in music, games, sports, business, or science? This question is the subject of one of psychology’s oldest debates.

The “debate” began sensibly enough:

In the late 1800s, Francis Galton—founder of the scientific study of intelligence and a cousin of Charles Darwin—analyzed the genealogical records of hundreds of scholars, artists, musicians, and other professionals and found that greatness tends to run in families. For example, he counted more than 20 eminent musicians in the Bach family. (Johann Sebastian was just the most famous.) Galton concluded that experts are “born.”

Then came the experts-are-made view and the 10,000-hour rule:

Nearly half a century later, the behaviorist John Watson countered that experts are “made” when he famously guaranteed that he could take any infant at random and “train him to become any type of specialist [he] might select—doctor, lawyer, artist, merchant-chief and, yes, even beggar-man and thief, regardless of his talents.”

The experts-are-made view has dominated the discussion in recent decades. In a pivotal 1993 article published in Psychological Review—psychology’s most prestigious journal—the Swedish psychologist K. Anders Ericsson and his colleagues proposed that performance differences across people in domains such as music and chess largely reflect differences in the amount of time people have spent engaging in “deliberate practice,” or training exercises specifically designed to improve performance…. For example, the average for elite violinists was about 10,000 hours, compared with only about 5,000 hours for the least accomplished group. In a second study, the difference for pianists was even greater—an average of more than 10,000 hours for experts compared with only about 2,000 hours for amateurs. Based on these findings, Ericsson and colleagues argued that prolonged effort, not innate talent, explained differences between experts and novices.

But reality has a way of making itself known:

[R]ecent research has demonstrated that deliberate practice, while undeniably important, is only one piece of the expertise puzzle—and not necessarily the biggest piece. In the first study to convincingly make this point, the cognitive psychologists Fernand Gobet and Guillermo Campitelli found that chess players differed greatly in the amount of deliberate practice they needed to reach a given skill level in chess. For example, the number of hours of deliberate practice to first reach “master” status (a very high level of skill) ranged from 728 hours to 16,120 hours. This means that one player needed 22 times more deliberate practice than another player to become a master.

A recent meta-analysis by Case Western Reserve University psychologist Brooke Macnamara and her colleagues (including the first author of this article for Slate) came to the same conclusion. We searched through more than 9,000 potentially relevant publications and ultimately identified 88 studies that collected measures of activities interpretable as deliberate practice and reported their relationships to corresponding measures of skill…. [P]eople who reported practicing a lot tended to perform better than those who reported practicing less. But the correlations were far from perfect: Deliberate practice left more of the variation in skill unexplained than it explained. For example, deliberate practice explained 26 percent of the variation for games such as chess, 21 percent for music, and 18 percent for sports. So, deliberate practice did not explain all, nearly all, or even most of the performance variation in these fields. In concrete terms, what this evidence means is that racking up a lot of deliberate practice is no guarantee that you’ll become an expert. Other factors matter.

Genes are among the other factors:

There is now compelling evidence that genes matter for success, too. In a study led by the King’s College London psychologist Robert Plomin, more than 15,000 twins in the United Kingdom were identified through birth records and recruited to perform a battery of tests and questionnaires, including a test of drawing ability in which the children were asked to sketch a person. In a recently published analysis of the data, researchers found that there was a stronger correspondence in drawing ability for the identical twins than for the fraternal twins. In other words, if one identical twin was good at drawing, it was quite likely that his or her identical sibling was, too. Because identical twins share 100 percent of their genes, whereas fraternal twins share only 50 percent on average, this finding indicates that differences across people in basic artistic ability are in part due to genes. In a separate study based on this U.K. sample, well over half of the variation between expert and less skilled readers was found to be due to genes.

In another study, a team of researchers at the Karolinska Institute in Sweden led by psychologist Miriam Mosing had more than 10,000 twins estimate the amount of time they had devoted to music practice and complete tests of basic music abilities, such as determining whether two melodies carry the same rhythm. The surprising discovery of this study was that although the music abilities were influenced by genes—to the tune of about 38 percent, on average—there was no evidence they were influenced by practice. For a pair of identical twins, the twin who practiced music more did not do better on the tests than the twin who practiced less. This finding does not imply that there is no point in practicing if you want to become a musician. The sort of abilities captured by the tests used in this study aren’t the only things necessary for playing music at a high level; things such as being able to read music, finger a keyboard, and commit music to memory also matter, and they require practice. But it does imply that there are limits on the transformative power of practice. As Mosing and her colleagues concluded, practice does not make perfect.

This is bad news for the blank-slate crowd on the left:

Ever since John Locke laid the groundwork for the Enlightenment by proposing that we are born as tabula rasa—blank slates—the idea that we are created equal has been the central tenet of the “modern” worldview. Enshrined as it is in the Declaration of Independence as a “self-evident truth,” this idea has special significance for Americans. Indeed, it is the cornerstone of the American dream—the belief that anyone can become anything they want with enough determination….

Wouldn’t it be better to just act as if we are equal, evidence to the contrary notwithstanding? That way, no people will be discouraged from chasing their dreams—competing in the Olympics or performing at Carnegie Hall or winning a Nobel Prize. The answer is no, for two reasons. The first is that failure is costly, both to society and to individuals. Pretending that all people are equal in their abilities will not change the fact that a person with an average IQ is unlikely to become a theoretical physicist, or the fact that a person with a low level of music ability is unlikely to become a concert pianist. It makes more sense to pay attention to people’s abilities and their likelihood of achieving certain goals, so people can make good decisions about the goals they want to spend their time, money, and energy pursuing…. Pushing someone into a career for which he or she is genetically unsuited will likely not work.

With regard to the latter point, Richard Sander has shown that aspiring blacks are chief among the victims of the form of “pushing” known as affirmative action. A few years ago, Sander was a guest blogger at The Volokh Conspiracy, where he posted thrice on the subject. In his first post, Sander writes:

As some readers will recall, a little more than seven years ago I published an analysis of law school affirmative action in the Stanford Law Review. The article was the first to present detailed data on the operation and effects of racial preferences in law schools (focusing on blacks).

I also laid out evidence suggesting that large preferences seemed to be worsening black outcomes. I argued that this was plausibly due to a “mismatch effect”; students receiving large preferences (for whatever reason) were likely to find themselves in academic environments where they had to struggle just to keep up; professor instruction would typically be aimed at the “median” student, so students with weaker academic preparation would tend to fall behind, and, even if they did not become discouraged and give up, would tend to learn less than they would have learned in an environment where their level of academic preparation was closer to the class median.

I suggested that the “mismatch effect” could explain as much as half of the black-white gap in first-time bar passage rates (the full gap is thirty to forty percentage points). I also suggested that “mismatch” might so worsen black outcomes that, on net, contemporary affirmative action was not adding to the total number of black lawyers, and might even be lowering the total number of new, licensed black attorneys.

This is from Sander’s second post:

Some of the most significant recent work on affirmative action concerns a phenomenon called “science mismatch”. The idea behind science mismatch is very intuitive: if you are a high school senior interested in becoming, for example, a chemist, you may seriously harm your chances of success by attending a school where most of the other would-be chemists have stronger academic preparation than you do. Professors will tend to pitch their class at the median student, not you; and if you struggle or fall behind in the first semester of inorganic chemistry, you will be in even worse shape in the second semester, and in very serious trouble when you hit organic chemistry. You are likely to get bad grades and to either transfer out of chemistry or fail to graduate altogether….

Duke economists Peter Arcidiacono, Esteban Aucejo, and Ken Spenner last year completed a study that looked at a number of ways that differences in admissions standards at Duke affected academic outcomes. In one of many useful analyses they did, they found that 54% of black men at Duke who, as freshmen, had been interested in STEM fields or economics, had switched out of those fields before graduation; the comparative rate for white men was 8%. Importantly, they found that “these cross-race differences in switching patterns can be fully explained by differences in academic background.” In other words, preferences – not race – was the culprit.

In research conducted by FTC economist Marc Luppino and me, using data from the University of California, we have found important peer effects and mismatch effects that affect students of all races; our results show that one’s chances of completing a science degree fall sharply, at a given level of academic preparation, as one attends more and more elite schools within the UC system. At Berkeley, there is a seven-fold difference in STEM degree completion between students with high and low pre-college credentials.

As is always the case with affirmative action, ironies abound. Although young blacks are about one-seventh as likely as young whites to eventually earn a Ph.D. in STEM fields, academically strong blacks in high school are more likely than similar whites to aspire to science careers. And although a U.S. Civil Rights Commission report in 2010 documented the “science mismatch” phenomenon in some detail, President Obama’s new initiative to improve the nation’s production of scientists neither recognizes nor addresses mismatch….

Science mismatch is, of course, relevant to the general affirmative action debate in showing that preferences can boomerang on their intended beneficiaries. But it also has a special relevance to Fisher v. University of Texas. The university’s main announced purpose in reintroducing racial preferences in 2004 was to increase “classroom” diversity. The university contended that, even though over a fifth of its undergraduates were black or Hispanic, many classrooms had no underrepresented minorities. It sought to use direct (and very large) racial preferences to increase campus URM numbers and thus increase the number of URMs in classes that lacked them. But science mismatch shows that this strategy, too, can be self-defeating. The larger a university’s preferences, the more likely it is that preferenced students will have trouble competing in STEM fields and other majors that are demanding and grade sternly. These students will tend to drop out of the tough fields and congregate in comparatively less demanding ones. Large preferences, in other words, can increase racial segregation across majors and courses within a university, and thus hurt classroom diversity.

And this is from Sander’s third post:

[In the previous post] I discussed a body of research – all of it uncontroverted – that documents a serious flaw in affirmative action programs pursued by elite colleges. Students who receive large preferences and arrive on campus hoping to major in STEM fields (e.g., Science, Technology, Engineering and Math) tend to migrate out of those fields at very high rates, or, if they remain in those fields, often either fail to graduate or graduate with very low GPAs. There is thus a strong tension between receiving a large admissions preference to a more elite school, and one’s ability to pursue a STEM career.

Is it possible for contemporary American universities to engage constructively with this type of research? …

Colleges and universities are committed to the mythology that diversity happens merely because they want it and put resources into it, and that all admitted students arrive with all the prerequisites necessary to flourish in any way they choose. Administrators work hard to conceal the actual differences in academic preparation that almost invariably accompany the aggressive use of preferences. Any research that documents the operation and effects of affirmative action therefore violates this “color-blind” mythology and accompanying norms; minority students are upset, correctly realizing that either the research is wrong or that administrators have misled them. In this scenario, administrators invariably resort to the same strategy: dismiss the research without actually lying about it; reassure the students that the researchers are misguided, but that the university can’t actually punish the researchers because of “academic freedom”….

Leftists — academic and other — cannot abide the truth when it refutes their prejudices. Affirmative action, as it turns out, is harmful to aspiring blacks. Most leftists will deny it because their leftist faith — their magical thinking– is more important to them than the well-being of those whose cause they claim to champion.


Evolution, Culture, and “Diversity”

The “satirical and opinionated,” but well-read, Fred Reed poses some questions about evolution. He wisely asks John Derbyshire to answer them. In the absence of a response from Derbyshire, I will venture some answers, and then offer some general observations about evolution and two closely related subjects: culture and “diversity.” (The “sneer quotes” mean that “diversity,” as used by leftists, really means favoritism toward their clientele — currently blacks and Hispanics, especially illegal immigrants).

Herewith, Reed’s questions (abridged, in italics) and my answers:

(1) In evolutionary principle, traits that lead to more surviving children proliferate. In practice, when people learn how to have fewer or no children, they do…. [W]hat selective pressures lead to a desire not to reproduce, and how does this fit into a Darwinian framework?

As life becomes less fraught for homo sapiens, reproduction becomes less necessary. First, the ability of the species (and families) to survive and thrive becomes less dependent on sheer numbers and more dependent on technological advances. Second (and consequently), more couples are able to  trade the time and expense of child-rearing for what would have been luxuries in times past (e.g., a nicer home, bigger cars, more luxurious vacations, a more comfortable retirement).

As suggested by the second point, human behavior isn’t determined solely by genes; it has a strong cultural component. There is an interplay between genes and culture, as I’ll discuss, but culture can (and does) influence evolution. An emergent aspect of culture is an inverse relationship between the number of children and social status. Social status is enhanced by the acquisition and display of goods made affordable by limiting family size.

(2) Morality. In evolution as I understand it, there are no absolute moral values: Morals evolved as traits allowing social cooperation, conducing to the survival of the group and therefore to the production of more surviving children….

Question: Why should I not indulge my hobby of torturing to death the severely genetically retarded? This would seem beneficial. We certainly don’t want them to reproduce, they use resources better invested in healthy children, and it makes no evolutionary difference whether they die quietly or screaming.

Here Reed clearly (if tacitly) acknowledges the role of culture as a (but not the) determinant of behavior. Morals may “evolve,” but not in the same way as physiological characteristics. Morals may nevertheless influence the survival of a species, as Reed suggests. Morals may also influence biological evolution to the extent that selective mating favors those who adhere to a beneficial morality, and yields offspring who are genetically predisposed toward that morality.

Religion — especially religion in the Judeo-Christian tradition — fosters beneficial morality. This is from David Sloan Wilson‘s “Beyond Demonic Memes: Why Richard Dawkins Is Wrong about Religion” (, July 4, 2007):

On average, religious believers are more prosocial than non-believers, feel better about themselves, use their time more constructively, and engage in long-term planning rather than gratifying their impulsive desires. On a moment-by-moment basis, they report being more happy, active, sociable, involved and excited. Some of these differences remain even when religious and non-religious believers are matched for their degree of prosociality. More fine-grained comparisons reveal fascinating differences between liberal vs. conservative protestant denominations, with more anxiety among the liberals and conservatives feeling better in the company of others than when alone…

In Darwin’s Cathedral, I initiated a survey of religions drawn at random from the 16-volume Encyclopedia of World Religions, edited by the great religious scholar Mircia Eliade. The results are described in an article titled “Testing Major Evolutionary Hypotheses about Religion with a Random Sample,” which was published in the journal Human Nature and is available on my website. The beauty of random sampling is that, barring a freak sampling accident, valid conclusions for the sample apply to all of the religions in the encyclopedia from which the sample was taken. By my assessment, the majority of religions in the sample are centered on practical concerns, especially the definition of social groups and the regulation of social interactions within and between groups. New religious movements usually form when a constituency is not being well served by current social organizations (religious or secular) in practical terms and is better served by the new movement. The seemingly irrational and otherworldly elements of religions in the sample usually make excellent practical sense when judged by the only gold standard that matters from an evolutionary perspective — what they cause the religious believers to do.

What religions do (on the whole) is to cause their adherents to live more positive and productive lives, as Wilson notes in the first part of the quotation.

Despite the decline of religious observance in the West, most Westerners are still strongly influenced by the moral tenets of the Judeo-Christian tradition. Why? Because the observance of those traditions fosters beneficial cooperation, and beneficial cooperation fosters happiness and prosperity. (For a detailed exposition of this point, see “Religion and Liberty” in “Facets of Liberty.”)

Therefore, one answer to Reed’s rhetorical question — “Why should I not indulge my hobby of torturing to death the severely genetically retarded?” — is that such behavior doesn’t comport with Judeo-Christian morality. A second answer is that empathy causes most people eschew actions that cause suffering in others (except in the defense of self, kin, and country), and empathy may be a genetic (i.e. evolutionary) trait.

(3) Abiogenesis. This is not going to be a fair question as there is no way anyone can know the answer, but I pose it anyway. The theory, which I cannot refute, is that a living, metabolizing, reproducing gadget formed accidentally in the ancient seas. Perhaps it did. I wasn’t there. It seems to me, though, that the more complex one postulates the First Critter to have been, the less likely, probably exponentially so, it would have been to form. The less complex one postulates it to have been, the harder to explain why biochemistry, which these days is highly sophisticated, cannot reproduce the event. Question: How many years would have to pass without replication of the event, if indeed it be not replicated, before one might begin to suspect that it didn’t happen?

How many years? 250 million to 1 billion. That’s roughly the length of time between the formation of Earth and the beginning of life, according to current estimates. (See the first paragraph of the Wikipedia article about abiogenesis.) That could be plenty of time for untold billions of random interactions of matter to have produced a life form that could, with further development, reproduce and become more complex. But who knows? And even if someone in a lab somewhere happens to produce such a “critter,” it may well be different than Reed’s First Critter.

I certainly hew to the possibility that seems to lurk in Reed’s mind; namely, that the First Critter was the handiwork of the Creator, or at least came to be because of the physical laws established by the Creator. (See “Existence and Creation,” possibility 5.)

(4) … Straight-line evolution, for example in which Eohippus gradually gets larger until it reaches Clydesdale, is plausible because each intervening step is a viable animal. In fact this is just selective breeding. Yet many evolutionary transformations seem to require intermediate stages that could not survive.

For example there are two-cycle bugs (insects, arachnids) that lay eggs that hatch into tiny replicas of the adults, which grow, lay eggs, and repeat the cycle. The four-cycle bugs go through egg, larva, pupa, adult. Question: What are the viable steps needed to evolve from one to the other? Or from anything to four-cycle? …

Lacking the technical wherewithal requisite to a specific answer, I fall back on time — the billions of years encompassed in evolution.

(5) … Mr. Derbyshire believes strongly in genetic determinism—that we are what we are and behave as we do because of genetic programming….

… A physical (to include chemical) system cannot make decisions. All subsequent states of a physical system are determined by the initial state. So, if one accepts the electrochemical premise (which, again, seems to be correct) it follows that we do not believe things because they are true, but because we are predestined to believe them. Question: Does not genetic determinism (with which I have no disagreement) lead to a  paradox: that the thoughts we think we are thinking we only think to be thoughts when they are really utterly predetermined by the inexorable working of physics and chemistry?

This smacks of Cartesian dualism, the view that “there are two fundamental kinds of substance: mental and material.” It seems to me easier to believe that the nervous system (with its focal point in the brain). It seems to me that experimental psychologists have amply document the links between brain activity (i.e., mental states) and behavior.

The real question is whether behavior is strictly determined by genes. The obvious answer is “no” because every instance of behavior is conditioned by immediate circumstances, which are not always (usually?) determined by the actor.

Further, free will is consistent with a purely physiological interpretation of behavioral decisions:

Suppose I think that I might want to eat some ice cream. I go to the freezer compartment and pull out an unopened half-gallon of vanilla ice cream and an unopened half-gallon of chocolate ice cream. I can’t decide between vanilla, chocolate, some of each, or none. I ask a friend to decide for me by using his random-number generator, according to rules of his creation. He chooses the following rules:

  • If the random number begins in an odd digit and ends in an odd digit, I will eat vanilla.
  • If the random number begins in an even digit and ends in an even digit, I will eat chocolate.
  • If the random number begins in an odd digit and ends in an even digit, I will eat some of each flavor.
  • If the random number begins in an even digit and ends in an odd digit, I will not eat ice cream.

Suppose that the number generated by my friend begins in an even digit and ends in an even digit: the choice is chocolate. I act accordingly.

I didn’t inevitably choose chocolate because of events that led to the present state of my body’s chemistry, which might otherwise have dictated my choice. That is, I broke any link between my past and my choice about a future action.

I call that free will.

I suspect that our brains are constructed in such a way as to produce the same kind of result in many situations, though certainly not in all situations. That is, we have within us the equivalent of an impartial friend and an (informed) decision-making routine, which together enable us to exercise something we can call free will.

My suspicion is well-founded. The brains of human beings are complex, and consist of many “centers” that perform different functions. That complexity enables self-awareness; a person may “stand back” from himself and view his actions critically. Human beings, in other words, aren’t simple machines that operate according hard-wired routines.

(6) … In principle, traits spread through a population because they lead to the having of greater numbers of children….

… Genes already exist in populations for extraordinary superiority of many sorts—for the intelligence of Stephen Hawking, the body of Mohammed Ali, for 20/5 vision, for the astonishing endurance in running of the Tarahumara Indians, and so on. To my unschooled understanding, these traits offer clear and substantial advantage in survival and reproduction, yet they do not become universal, or even common. The epicanthic fold does. Question: Why do seemingly trivial traits proliferate while clearly important ones do not?

First, survival depends on traits that are suited to the environment in which a group finds itself. Not all — or even most — challenges to survival demand the intelligence of a Hawking, the body of an Ali, etc. Further, cooperative groups find that acting together they possess high intelligence of a kind that’s suited to the group’s situation. Similarly, the strength of many is usually sufficient to overcome obstacles and meet challenges.

Second, mating isn’t driven entirely by a focus on particular traits — high intelligence, superior athletic ability, etc. Such traits therefore remain relatively rare unless they are essential to survival, which might explain the “astonishing endurance running of the Tarahumara Indians.”

(7) … Looking at the human body, I see many things that appear to have no relation to survival or more vigorous reproduction, and that indeed work against it, yet are universal in the species. For example, the kidneys contain the nervous tissue that makes kidney stones agonizingly painful, yet until recently the victim has been able to do nothing about them….

What is the reproductive advantage of crippling pain (migraines can be crippling) about which pre-recently, the sufferer could do nothing?

What is the reproductive advantage of Tay-Sachs disease, which is found disproportionately among Ashkenazi Jews? Here is a reasonable hypothesis:

Gregory Cochran proposes that the mutant alleles causing Tay–Sachs confer higher intelligence when present in carrier form, and provided a selective advantage in the historical period when Jews were restricted to intellectual occupations.[9][10] Peter Frost argues for a similar heterozygote advantage for mutant alleles being responsible for the prevalence of Tay Sachs disease in Eastern Quebec.[11]

In sum, the bad sometimes goes with the good. That’s just the way evolution is. In the case of migraines, it may be that those who are prone to them are also in some way attractive as mates. Who knows? But if every genetic disadvantage worked against survival, human beings would have become extinct long ago.

(8) Finally, the supernatural. Unfairly, as it turned out, in regard to religion I had expected Mr. Derbyshire to strike the standard “Look at me, I’m an atheist, how advanced I am” pose. I was wrong. In fact he says that he believes in a God. (Asked directly, he responded, “Yes, to my own satisfaction, though not necessarily to yours.”) His views are reasoned, intellectually modest, and, though I am not a believer, I see nothing with which to quarrel, though for present purposes this is neither here nor there. Question: If one believes in or suspects the existence of God or gods, how does one exclude the possibility that He, She, or It meddles in the universe—directing evolution, for example?

A belief in gods would seem to leave the door open to Intelligent Design, the belief that the intricacies of life came about not by accident but were crafted by Somebody or Something. The view, anathema in evolutionary circles, is usually regarded as emanating from Christianity, and usually does….

In the piece by Derbyshire to which Reed links, Derbyshire writes:

I belong to the 16 percent of Americans who, in the classification used for a recent survey, believe in a “Critical God.”… He is the Creator….

I am of the same persuasion, though Derbyshire and I may differ in our conception of God’s role in the Universe:

1. There is necessarily a creator of the universe [see this], which comprises all that exists in “nature.”

2. The creator is not part of nature; that is, he stands apart from his creation and is neither of its substance nor governed by its laws. (I use “he” as a term of convenience, not to suggest that the creator is some kind of human or animate being, as we know such beings.)

3. The creator designed the universe, if not in detail then in its parameters. The parameters are what we know as matter-energy (substance) and its various forms, motions, and combinations (the laws that govern the behavior of matter-energy).

4. The parameters determine everything that is possible in the universe. But they do not necessarily dictate precisely the unfolding of events in the universe. Randomness and free will are evidently part of the creator’s design.

5. The human mind and its ability to “do science” — to comprehend the laws of nature through observation and calculation — are artifacts of the creator’s design.

6. Two things probably cannot be known through science: the creator’s involvement in the unfolding of natural events; the essential character of the substance on which the laws of nature operate.

Points 3 and 4 say as much as I am willing to say about Intelligent Design.

I turn now to the interaction of culture and biological evolution, which figures in my answers to several of Reed’s questions. Consider this, from an article by evolutionary psychologist Joseph Henrich (“A Cultural Species: How Culture Drove Human Evolution,” Psychological Science Agenda, American Psychological Association, November 2011; citations omitted):

Once a species is sufficiently reliant on learning from others for at least some aspects of its behavioral repertoire, cultural evolutionary processes can arise, and these processes can alter the environment faced by natural selection acting on genes….

Models of cumulative cultural evolution suggest two important, and perhaps non-intuitive, features of our species. First, our ecological success, technology, and adaptation to diverse environments is not due to our intelligence. Alone and stripped of our culture, we are hopeless as a species. Cumulative cultural evolution has delivered both our fancy technologies as well as the subtle and unconscious ways that humans have adapted their behavior and thinking to tackle environmental challenges. The smartest among us could not in a single lifetime devise even a small fraction of the techniques and technologies that allow any foraging society to survive. Second, the available formal models make clear that the effectiveness of this cumulative cultural evolutionary process depends crucially on the size and interconnectedness of our populations and social networks. It’s the ability to freely exchange information that sparks and accelerates adaptive cultural evolution, and creates innovation…. Sustaining complex technologies depends on maintaining a large and well-interconnected population of minds.

…In the case of ethnic groups, for example, such models explore how genes and culture coevolve. This shows how cultural evolution will, under a wide range of conditions, create a landscape in which different social groups tend to share both similar behavioral expectations and similar arbitrary “ethnic markers” (like dialect or language). In the wake of this culturally constructed world, genes evolve to create minds that are inclined to preferentially interact with and imitate those who share their markers. This guarantees that individuals most effectively coordinate with those who share their culturally learned behavioral expectations (say about marriage or child rearing). These purely theoretical predictions were subsequently confirmed by experiments with both children and adults.

This approach also suggests that cultural evolution readily gives rise to social norms, as long as learners can culturally acquire the standards by which they judge others. Many models robustly demonstrate that cultural evolution can sustain almost any behavior or preference that is common in a population (including cooperation), if it is not too costly. This suggests that different groups will end up with different norms and begin to compete with each other. Competition among groups with different norms will favor those particular norms that lead to success in intergroup competition. My collaborators and I have argued that cultural group selection has shaped the cultural practices, institutions, beliefs and psychologies that are common in the world today, including those associated with anonymous markets, prosocial religions with big moralizing gods, and monogamous marriage. Each of these cultural packages, which have emerged relatively recently in human history, impacts our psychology and behavior. Priming “markets” and “God”, for example, increase trust and giving (respectively) in behavioral experiments, though “God primes” only work on theists. Such research avenues hold the promise of explaining, rather than merely documenting, the patterns of psychological variation observed across human populations.

The cultural evolution of norms over tens or hundreds of thousands of years, and their shaping by cultural group selection, may have driven genetic evolution to create a suite of cognitive adaptations we call norm psychology. This aspect of our evolved psychology emerged and coevolved in response to cultural evolution’s production of norms. This suite facilitates, among other things, our identification and learning of social norms, our expectation of sanctions for norm violations, and our ability to internalize normative behavior as motivations….

Biological evolution continues, and with it, cultural evolution. But there are some “constants” that seem to remain embedded in the norms of most cultural-genetic groups. Among them, moral codes that exclude gratuitous torture of innocent children, a belief in God, and status-consciousness (which, for example, reinforces a diminished need to reproduce for survival of the species).

Henrich hits upon one of the reasons — perhaps the main reason — why efforts to integrate various biological-cultural groups under the banner of “diversity” are doomed to failure:

[G]enes evolve to create minds that are inclined to preferentially interact with and imitate those who share their markers. This guarantees that individuals most effectively coordinate with those who share their culturally learned behavioral expectations (say about marriage or child rearing).

As I say here,

genetic kinship will always be a strong binding force, even where the kinship is primarily racial. Racial kinship boundaries, by the way, are not always and necessarily the broad ones suggested by the classic trichotomy of Caucasoid, Mongoloid, Negroid. (If you want to read for yourself about the long, convoluted, diffuse, and still controversial evolutionary chains that eventuated in the sub-species homo sapiens sapiens, to which all humans are assigned arbitrarily, without regard for their distinctive differences, begin here, here, here, and here.)

The obverse of of genetic kinship is “diversity,” which often is touted as a good thing by anti-tribalist social engineers. But “diversity” is not a good thing when it comes to social bonding.

At that point, I turn to an article by Michael Jonas about a study by Harvard political scientist Robert Putnam, “E Pluribus Unum: Diversity and Community in the Twenty-first Century“:

It has become increasingly popular to speak of racial and ethnic diversity as a civic strength. From multicultural festivals to pronouncements from political leaders, the message is the same: our differences make us stronger.

But a massive new study, based on detailed interviews of nearly 30,000 people across America, has concluded just the opposite. Harvard political scientist Robert Putnam — famous for “Bowling Alone,” his 2000 book on declining civic engagement — has found that the greater the diversity in a community, the fewer people vote and the less they volunteer, the less they give to charity and work on community projects. In the most diverse communities, neighbors trust one another about half as much as they do in the most homogenous settings. The study, the largest ever on civic engagement in America, found that virtually all measures of civic health are lower in more diverse settings….

…Putnam’s work adds to a growing body of research indicating that more diverse populations seem to extend themselves less on behalf of collective needs and goals….

(That’s from Jonas’s article, “The Downside of diversity,” The Boston Globe (, August 5, 2007. See this post for more about genetic kinship and “diversity.”)

In a later post, I add this:

Yes, human beings are social animals, but human beings are not “brothers under the skin,” and there is no use in pretending that we are. Trying to make us so, by governmental fiat, isn’t only futile but also wasteful and harmful. The futility of forced socialization is as true of the United States — a vast and varied collection of races, ethnicities, religions, and cultures — as it is of the world.

Despite the blatant reality of America’s irreconcilable diversity, American increasingly are being forced to lead their lives according to the dictates of the central government. Some apologists for this state of affairs will refer to the “common good,” which is a fiction that I address in [“Modern Utilitarianism,” “The Social Welfare Function,” and “Utilitarianism vs. Liberty”].

Human beings, for the most part, may be bigger, stronger, and healthier than ever, but their physical progress depends heavily on technology, and would be reversed by a cataclysm that disables technology. Further, technologically based prosperity masks moral squalor. Strip away that prosperity, and the West would look like the warring regions of Central and South America, Eastern Europe, the Middle East, Africa, and South and Southeast Asia: racial and ethnic war without end. Much of urban and suburban America — outside affluent, well-guarded, and mostly “liberal” enclaves — would look like Ferguson.

Human beings are not “brothers under the skin,” and no amount of wishful thinking or forced integration can make us so. That is the lesson to be learned from biological and cultural evolution, which makes human beings different — perhaps irreconcilably so — but not necessarily better.


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Related posts:
Crime, Explained
Society and the State
Race and Reason: The Victims of Affirmative Action
Race and Reason: The Achievement Gap — Causes and Implications
Liberty and Society
Tolerance on the Left
The Eclipse of “Old America”
Genetic Kinship and Society
“Conversing” about Race
The Fallacy of Human Progress
“We the People” and Big Government
Evolution and Race
The Social Animal and the “Social Contract”
“Wading” into Race, Culture, and IQ
Poverty, Crime, and Big Government

Poverty, Crime, and Big Government

Dr. James Thompson (Psychological Comments) reports the results of a thorough study of the link between poverty and crime. Near the end of the piece, Dr. Thompson quotes The Economist‘s summary of the study’s implications:

That suggests two, not mutually exclusive, possibilities. One is that a family’s culture, once established, is “sticky”—that you can, to put it crudely, take the kid out of the neighbourhood, but not the neighbourhood out of the kid. Given, for example, children’s propensity to emulate elder siblings whom they admire, that sounds perfectly plausible. The other possibility is that genes which predispose to criminal behaviour (several studies suggest such genes exist) are more common at the bottom of society than at the top, perhaps because the lack of impulse-control they engender also tends to reduce someone’s earning capacity.

Neither of these conclusions is likely to be welcome to social reformers. The first suggests that merely topping up people’s incomes, though it may well be a good idea for other reasons, will not by itself address questions of bad behaviour. The second raises the possibility that the problem of intergenerational poverty may be self-reinforcing, particularly in rich countries like Sweden where the winnowing effects of education and the need for high levels of skill in many jobs will favour those who can control their behaviour, and not those who rely on too many chemical crutches to get them through the day.

In brief, there is a strong connection between genes and criminal behavior. Inasmuch as there are also strong connections between genes and intelligence, on the one hand, and intelligence and income, on the other hand, it follows that:

  • Criminal behavior will be more prevalent in genetic groups with below-average intelligence.
  • Poverty will be more prevalent in genetic groups with below-average intelligence.
  • The correlation between crime and poverty must, therefore, reflect (to some extent) the correlation between below-average intelligence and poverty.

As The Economist notes “merely topping up people’s incomes … will not by itself address questions of bad behaviour.” This would seem to contradict my finding of a strongly negative relationship between economic growth and the rate of violent-and-property crime.

But there is no contradiction. Not all persons who commit crimes are incorrigible. At the margin, there are persons who will desist from criminal activity when presented with the alternative of attaining money without running the risk of being punished for their efforts.

How much less crime would there be if economic growth weren’t suppressed by the dead hand of big government? A lot less.

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Related posts:
Crime, Explained
Lock ‘Em Up
Estimating the Rahn Curve: Or, How Government Spending Inhibits Economic Growth
Race and Reason: The Achievement Gap — Causes and Implications
“Conversing” about Race
Evolution and Race
“Wading” into Race, Culture, and IQ

Not-So-Random Thoughts (X)

Links to the other posts in this occasional series may be found at “Favorite Posts,” just below the list of topics.

How Much Are Teachers Worth?

David Harsanyi writes:

“The bottom line,” says the Center for American Progress, “is that mid- and late-career teachers are not earning what they deserve, nor are they able to gain the salaries that support a middle-class existence.”

Alas, neither liberal think tanks nor explainer sites have the capacity to determine the worth of human capital. And contrasting the pay of a person who has a predetermined government salary with the pay earned by someone in a competitive marketplace tells us little. Public-school teachers’ compensation is determined by contracts negotiated long before many of them even decided to teach. These contracts hurt the earning potential of good teachers and undermine the education system. And it has nothing to do with what anyone “deserves.”

So if teachers believe they aren’t making what they’re worth — and they may well be right about that — let’s free them from union constraints and let them find out what the job market has to offer. Until then, we can’t really know. Because a bachelor’s degree isn’t a dispensation from the vagaries of economic reality. And teaching isn’t the first step toward sainthood. Regardless of what you’ve heard. (“Are Teachers Underpaid? Let’s Find Out,”, July 25, 2014)

Harsanyi is right, but too kind. Here’s my take, from “The Public-School Swindle“:

[P]ublic “education” — at all levels — is not just a rip-off of taxpayers, it is also an employment scheme for incompetents (especially at the K-12 level) and a paternalistic redirection of resources to second- and third-best uses.

And, to top it off, public education has led to the creation of an army of left-wing zealots who, for many decades, have inculcated America’s children and young adults in the advantages of collective, non-market, anti-libertarian institutions, where paternalistic “empathy” supplants personal responsibility.

Utilitarianism, Once More

EconLog bloggers Bryan Caplan and Scott Sumner are enjoying an esoteric exchange about utilitarianism (samples here and here), which is a kind of cost-benefit calculus in which the calculator presumes to weigh the costs and benefits that accrue to other persons.  My take is that utilitarianism borders on psychopathy. In “Utilitarianism and Psychopathy,” I quote myself to this effect:

Here’s the problem with cost-benefit analysis — the problem it shares with utilitarianism: One person’s benefit can’t be compared with another person’s cost. Suppose, for example, the City of Los Angeles were to conduct a cost-benefit analysis that “proved” the wisdom of constructing yet another freeway through the city in order to reduce the commuting time of workers who drive into the city from the suburbs.

Before constructing the freeway, the city would have to take residential and commercial property. The occupants of those homes and owners of those businesses (who, in many cases would be lessees and not landowners) would have to start anew elsewhere. The customers of the affected businesses would have to find alternative sources of goods and services. Compensation under eminent domain can never be adequate to the owners of taken property because the property is taken by force and not sold voluntarily at a true market price. Moreover, others who are also harmed by a taking (lessees and customers in this example) are never compensated for their losses. Now, how can all of this uncompensated cost and inconvenience be “justified” by, say, the greater productivity that might (emphasize might) accrue to those commuters who would benefit from the construction of yet another freeway.

Yet, that is how cost-benefit analysis works. It assumes that group A’s cost can be offset by group B’s benefit: “the greatest amount of happiness altogether.”

America’s Financial Crisis

Timothy Taylor tackles the looming debt crisis:

First, the current high level of government debt, and the projections for the next 25 years, mean that the U.S. government lacks fiscal flexibility….

Second, the current spending patterns of the U.S. government are starting to crowd out everything except health care, Social Security, and interest payments….

Third, large government borrowing means less funding is available for private investment….

…CBO calculates an “alternative fiscal scenario,” in which it sets aside some of these spending and tax changes that are scheduled to take effect in five years or ten years or never…. [T]he extended baseline scenario projected that the debt/GDP ratio would be 106% by 2039. In the alternative fiscal scenario, the debt-GDP ratio is projected to reach 183% of GDP by 2039. As the report notes: “CBO’s extended alternative fiscal scenario is based on the assumptions that certain policies that are now in place but are scheduled to change under current law will be continued and that some provisions of law that might be difficult to sustain for a long period will be modified. The scenario, therefore, captures what some analysts might consider to be current policies, as opposed to current laws.”…

My own judgement is that the path of future budget deficits in the next decade or so is likely to lean toward the alternative fiscal scenario. But long before we reach a debt/GDP ratio of 183%, something is going to give. I don’t know what will change. But as an old-school economist named Herb Stein used to say, “If something can’t go on, it won’t.” (Long Term Budget Deficits,Conversable Economist, July 24, 2014)

Professional economists are terribly low-key, aren’t they? Here’s the way I see it, in “America’s Financial Crisis Is Now“:

It will not do simply to put an end to the U.S. government’s spending spree; too many State and local governments stand ready to fill the void, and they will do so by raising taxes where they can. As a result, some jurisdictions will fall into California- and Michigan-like death-spirals while jobs and growth migrate to other jurisdictions…. Even if Congress resists the urge to give aid and comfort to profligate States and municipalities at the expense of the taxpayers of fiscally prudent jurisdictions, the high taxes and anti-business regimes of California- and Michigan-like jurisdictions impose deadweight losses on the whole economy….

So, the resistance to economically destructive policies cannot end with efforts to reverse the policies of the federal government. But given the vast destructiveness of those policies — “entitlements” in particular — the resistance must begin there. Every conservative and libertarian voice in the land must be raised in reasoned opposition to the perpetuation of the unsustainable “promises” currently embedded in Social Security, Medicare, and Medicaid — and their expansion through Obamacare. To those voices must be added the voices of “moderates” and “liberals” who see through the proclaimed good intentions of “entitlements” to the economic and libertarian disaster that looms if those “entitlements” are not pared down to their original purpose: providing a safety net for the truly needy.

The alternative to successful resistance is stark: more borrowing, higher interest payments, unsustainable debt, higher taxes, and economic stagnation (at best).

For the gory details about government spending and economic stagnation, see “Estimating the Rahn Curve: Or, How Government Spending Inhibits Economic Growth” and “The True Multiplier.”

Climate Change: More Evidence against the Myth of AGW

There are voices of reason, that is, real scientists doing real science:

Over the 55-years from 1958 to 2012, climate models not only significantly over-predict observed warming in the tropical troposphere, but they represent it in a fundamentally different way than is observed. (Ross McKittrick and Timothy Vogelsang, “Climate models not only significantly over-predict observed warming in the tropical troposphere, but they represent it in a fundamentally different way than is observed,” excerpted at Watt’s Up With That, July 24, 2014)

Since the 1980s anthropogenic aerosols have been considerably reduced in Europe and the Mediterranean area. This decrease is often considered as the likely cause of the brightening effect observed over the same period. This phenomenon is however hardly reproduced by global and regional climate models. Here we use an original approach based on reanalysis-driven coupled regional climate system modelling, to show that aerosol changes explain 81 ± 16 per cent of the brightening and 23 ± 5 per cent of the surface warming simulated for the period 1980–2012 over Europe. The direct aerosol effect is found to dominate in the magnitude of the simulated brightening. The comparison between regional simulations and homogenized ground-based observations reveals that observed surface solar radiation, as well as land and sea surface temperature spatio-temporal variations over the Euro-Mediterranean region are only reproduced when simulations include the realistic aerosol variations. (“New paper finds 23% of warming in Europe since 1980 due to clean air laws reducing sulfur dioxide,” The Hockey Schtick, July 23, 2014)

My (somewhat out-of-date but still useful) roundup of related posts and articles is at “AGW: The Death Knell.”

Crime Explained…

…but not by this simplistic item:

Of all of the notions that have motivated the decades-long rise of incarceration in the United States, this is probably the most basic: When we put people behind bars, they can’t commit crime.

The implied corollary: If we let them out, they will….

Crime trends in a few states that have significantly reduced their prison populations, though, contradict this fear. (Emily Badger, “There’s little evidence that fewer prisoners means more crime,” Wonkblog, The Washington Post, July 21, 2014)

Staring at charts doesn’t yield answers to complex, multivariate questions, such as the causes of crime. Ms. Badger should have extended my work of seven years ago (“Crime, Explained“). Had she, I’m confident that she would have obtained the same result, namely:

VPC (violent+property crimes per 100,000 persons) =


+346837BLK (number of blacks as a decimal fraction of the population)

-3040.46GRO (previous year’s change in real GDP per capita, as a decimal fraction of the base)

-1474741PRS (the number of inmates in federal and State prisons in December of the previous year, as a decimal fraction of the previous year’s population)

The t-statistics on the intercept and coefficients are 19.017, 21.564, 1.210, and 17.253, respectively; the adjusted R-squared is 0.923; the standard error of the estimate/mean value of VPC = 0.076.

The coefficient and t-statistic for PRS mean that incarceration has a strong, statistically significant, negative effect on the violent-property crime rate. In other words, more prisoners = less crime against persons and their property.

The Heritability of Intelligence

Strip away the trappings of culture and what do you find? This:

If a chimpanzee appears unusually intelligent, it probably had bright parents. That’s the message from the first study to check if chimp brain power is heritable.

The discovery could help to tease apart the genes that affect chimp intelligence and to see whether those genes in humans also influence intelligence. It might also help to identify additional genetic factors that give humans the intellectual edge over their non-human-primate cousins.

The researchers estimate that, similar to humans, genetic differences account for about 54 per cent of the range seen in “general intelligence” – dubbed “g” – which is measured via a series of cognitive tests. “Our results in chimps are quite consistent with data from humans, and the human heritability in g,” says William Hopkins of the Yerkes National Primate Research Center in Atlanta, Georgia, who heads the team reporting its findings in Current Biology.

“The historical view is that non-genetic factors dominate animal intelligence, and our findings challenge that view,” says Hopkins. (Andy Coghlan, “Chimpanzee brain power is strongly heritable,New Scientist, July 10, 2014)

Such findings are consistent with Nicholas Wade’s politically incorrect A Troublesome Inheritance: Genes, Race and Human History. For related readings, see “‘Wading’ into Race, Culture, and IQ’.” For a summary of scholarly evidence about the heritability of intelligence — and its dire implications — see “Race and Reason — The Achievement Gap: Causes and Implications.” John Derbyshire offers an even darker view: “America in 2034” (American Renaissance, June 9, 2014).

The correlation of race and intelligence is, for me, an objective matter, not an emotional one. For evidence of my racial impartiality, see the final item in “My Moral Profile.”

The Limits of Science, Illustrated by Scientists

Our first clue is the title of a recent article in The Christian Science Monitor: “Why the Universe Isn’t Supposed to Exist.” The article reads, in part:

The universe shouldn’t exist — at least according to a new theory.

Modeling of conditions soon after the Big Bang suggests the universe should have collapsed just microseconds after its explosive birth, the new study suggests.

“During the early universe, we expected cosmic inflation — this is a rapid expansion of the universe right after the Big Bang,” said study co-author Robert Hogan, a doctoral candidate in physics at King’s College in London. “This expansion causes lots of stuff to shake around, and if we shake it too much, we could go into this new energy space, which could cause the universe to collapse.”

Physicists draw that conclusion from a model that accounts for the properties of the newly discovered Higgs boson particle, which is thought to explain how other particles get their mass; faint traces of gravitational waves formed at the universe’s origin also inform the conclusion.

Of course, there must be something missing from these calculations.

“We are here talking about it,” Hogan told Live Science. “That means we have to extend our theories to explain why this didn’t happen.”

No kidding!

So, you think “the science is settled,” do you? Think again, long and hard.

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Related posts: Just about everything here. Enjoy.


Verbal Regression Analysis, the “End of History,” and Think-Tanks

There once was a Washington DC careerist with whom I crossed verbal swords. I won; he lost and moved on to another job. I must, however, credit him with at least one accurate observation: Regression analysis is a method of predicting the past with great accuracy.

What did he mean by that? Data about past events may yield robust statistical relationships, but those relationships are meaningless unless they accurately predict future events. The problem is that in the go-go world of DC, where rhetoric takes precedence over reality, analysts usually assume the predictive power of statistical relationships, without waiting to see if they have any bearing on future events.

Francis Fukuyama has just published an article in which he admits that his famous article, “The End of History” (1989), was a kind of verbal regression analysis — a sweeping prediction of the future based on a (loose) verbal analysis of the past.

What is the “end of history”? This, according to Wikipedia:

[A] political and philosophical concept that supposes that a particular political, economic, or social system may develop that would constitute the end-point of humanity’s sociocultural evolution and the final form of human government.

What did Fukuyama say about “the end of history” in 1989? This:

In watching the flow of events over the past decade or so, it is hard to avoid the feeling that something very fundamental has happened in world history….

What we may be witnessing in not just the end of the Cold War, or the passing of a particular period of post-war history, but the end of history as such: that is, the end point of mankind’s ideological evolution and the universalization of Western liberal democracy as the final form of human government. This is not to say that there will no longer be events to fill the pages of Foreign Affairs‘s yearly summaries of international relations, for the victory of liberalism has occurred primarily in the realm of ideas or consciousness and is as yet incomplete in the real or material world. But there are powerful reasons for believing that it is the ideal that will govern the material world in the long run. To understand how this is so, we must first consider some theoretical issues concerning the nature of historical change.

What does Fukuyama say now? This:

I argued [in 1989] that History (in the grand philosophical sense) was turning out very differently from what thinkers on the left had imagined. The process of economic and political modernization was leading not to communism, as the Marxists had asserted and the Soviet Union had avowed, but to some form of liberal democracy and a market economy. History, I wrote, appeared to culminate in liberty: elected governments, individual rights, an economic system in which capital and labor circulated with relatively modest state oversight….

Twenty-five years later, the most serious threat to the end-of-history hypothesis isn’t that there is a higher, better model out there that will someday supersede liberal democracy; neither Islamist theocracy nor Chinese capitalism cuts it. Once societies get on the up escalator of industrialization, their social structure begins to change in ways that increase demands for political participation. If political elites accommodate these demands, we arrive at some version of democracy.

The question is whether all countries will inevitably get on that escalator. The problem is the intertwining of politics and economics. Economic growth requires certain minimal institutions such as enforceable contracts and reliable public services before it will take off, but those basic institutions are hard to create in situations of extreme poverty and political division. Historically, societies broke out of this “trap” through accidents of history, in which bad things (like war) often created good things (like modern governments). It is not clear, however, that the stars will necessarily align for everyone….

A second problem that I did not address 25 years ago is that of political decay, which constitutes a down escalator. All institutions can decay over the long run. They are often rigid and conservative; rules responding to the needs of one historical period aren’t necessarily the right ones when external conditions change.

Moreover, modern institutions designed to be impersonal are often captured by powerful political actors over time. The natural human tendency to reward family and friends operates in all political systems, causing liberties to deteriorate into privileges….

As for technological progress, it is fickle in distributing its benefits. Innovations such as information technology spread power because they make information cheap and accessible, but they also undermine low-skill jobs and threaten the existence of a broad middle class.

No one living in an established democracy should be complacent about its survival. But despite the short-term ebb and flow of world politics, the power of the democratic ideal remains immense. We see it in the mass protests that continue to erupt unexpectedly from Tunis to Kiev to Istanbul, where ordinary people demand governments that recognize their equal dignity as human beings. We also see it in the millions of poor people desperate to move each year from places like Guatemala City or Karachi to Los Angeles or London.

Even as we raise questions about how soon everyone will get there, we should have no doubt as to what kind of society lies at the end of History.

And blah, blah, blah, blah, blah.

The “end of history” will be some kind of “democracy,” and it will arrive despite all of the very real obstacles in its way, which include sectional and sectarian conflict, the capture of governmental power by special interests, and economic realities (which are somehow “wrong,” despite the fact that they are just realities). In the end “hope and change” will prevail because, well, they ought to prevail, by golly.

In sum, Fukuyama has substituted a new verbal regression analysis for his old one.

You may have guessed by now that “verbal regression analysis” means “bullshit.” Fukuyama emitted bullshit in 1989, and he’s emitting it 25 years later. Why anyone would pay attention to him and his ilk is beyond me.

But there are organizations — so-called think-tanks — that specialize in converting your tax dollars into bullshit of the kind emitted by Fukuyama. It’s unfortunate that the output of those think-tanks can’t be bagged and used as fertilizer. It would then have real value.

“Settled Science” and the Monty Hall Problem

The so-called 97-percent consensus among climate scientists about anthropogenic global warming (AGW) isn’t evidence of anything but the fact that scientists are only human. Even if there were such a consensus, it certainly wouldn’t prove the inchoate theory of AGW, any more than the early consensus against Einstein’s special theory of relativity disproved that theory.

Actually, in the case of AGW, the so-called consensus is far from a consensus about the extent of warming, its causes, and its implications. (See, for example, this post and this one.) But it’s undeniable that a lot of climate scientists believe in a “strong” version of AGW, and in its supposedly dire consequences for humanity.

Why is that? Well, in a field as inchoate as climate science, it’s easy to let one’s prejudices drive one’s research agenda and findings, even if only subconsciously. And isn’t it more comfortable and financially rewarding to be with the crowd and where the money is than to stand athwart the conventional wisdom? (Lennart Bengtsson certainly found that to be the case.) Moreover, there was, in the temperature records of the late 20th century, a circumstantial case for AGW, which led to the development of theories and models that purport to describe a strong relationship between temperature and CO2. That the theories and models are deeply flawed and lacking in predictive value seems not to matter to the 97 percent (or whatever the number is).

In other words, a lot of climate scientists have abandoned the scientific method, which demands skepticism, in order to be on the “winning” side of the AGW issue. How did it come to be thought of as the “winning” side? Credit vocal so-called scientists who were and are (at least) guilty of making up models to fit their preconceptions, and ignoring evidence that human-generated CO2 is a minor determinant of atmospheric temperature. Credit influential non-scientists (e.g., Al Gore) and various branches of the federal government that have spread the gospel of AGW and bestowed grants on those who can furnish evidence of it. Above all, credit the media, which for the past two decades has pumped out volumes of biased, half-baked stories about AGW, in the service of the “liberal” agenda: greater control of the lives and livelihoods of Americans.

Does this mean that the scientists who are on the AGW bandwagon don’t believe in the correctness of AGW theory? I’m sure that most of them do believe in it — to some degree. They believe it at least to the same extent as a religious convert who zealously proclaims his new religion to prove (mainly to himself) his deep commitment to that religion.

What does all of this have to do with the Monty Hall problem? This:

Making progress in the sciences requires that we reach agreement about answers to questions, and then move on. Endless debate (think of global warming) is fruitless debate. In the Monty Hall case, this social process has actually worked quite well. A consensus has indeed been reached; the mathematical community at large has made up its mind and considers the matter settled. But consensus is not the same as unanimity, and dissenters should not be stifled. The fact is, when it comes to matters like Monty Hall, I’m not sufficiently skeptical. I know what answer I’m supposed to get, and I allow that to bias my thinking. It should be welcome news that a few others are willing to think for themselves and challenge the received doctrine. Even though they’re wrong. (Brian Hayes, “Monty Hall Redux” (a book review), American Scientist, September-October 2008)

The admirable part of Hayes’s statement is its candor: Hayes admits that he may have adopted the “consensus” answer because he wants to go with the crowd.

The dismaying part of Hayes’s statement is his smug admonition to accept “consensus” and move on. As it turns out the “consensus” about the Monty Hall problem isn’t what it’s cracked up to be. A lot of very bright people have solved a tricky probability puzzle, but not the Monty Hall problem. (For the details, see my post, “The Compleat Monty Hall Problem.”)

And the “consensus” about AGW is very far from being the last word, despite the claims of true believers. (See, for example, the relatively short list of recent articles, posts, and presentations given at the end of this post.)

Going with the crowd isn’t the way to do science. It’s certainly not the way to ascertain the contribution of human-generated CO2 to atmospheric warming, or to determine whether the effects of any such warming are dire or beneficial. And it’s most certainly not the way to decide whether AGW theory implies the adoption of policies that would stifle economic growth and hamper the economic betterment of millions of Americans and billions of other human beings — most of whom would love to live as well as the poorest of Americans.

Given the dismal track record of global climate models, with their evident overstatement of the effects of CO2 on temperatures, there should be a lot of doubt as to the causes of rising temperatures in the last quarter of the 20th century, and as to the implications for government action. And even if it could be shown conclusively that human activity will temperatures to resume the rising trend of the late 1900s, several important questions remain:

  • To what extent would the temperature rise be harmful and to what extent would it be beneficial?
  • To what extent would mitigation of the harmful effects negate the beneficial effects?
  • What would be the costs of mitigation, and who would bear those costs, both directly and indirectly (e.g., the effects of slower economic growth on the poorer citizens of thw world)?
  • If warming does resume gradually, as before, why should government dictate precipitous actions — and perhaps technologically dubious and economically damaging actions — instead of letting households and businesses adapt over time by taking advantage of new technologies that are unavailable today?

Those are not issues to be decided by scientists, politicians, and media outlets that have jumped on the AGW bandwagon because it represents a “consensus.” Those are issues to be decided by free, self-reliant, responsible persons acting cooperatively for their mutual benefit through the mechanism of free markets.

*     *     *

Recent Related Reading:
Roy Spencer, “95% of Climate Models Agree: The Observations Must Be Wrong,” Roy Spencer, Ph.D., February 7, 2014
Roy Spencer, “Top Ten Good Skeptical Arguments,” Roy Spencer, Ph.D., May 1, 2014
Ross McKittrick, “The ‘Pause’ in Global Warming: Climate Policy Implications,” presentation to the Friends of Science, May 13, 2014 (video here)
Patrick Brennan, “Abuse from Climate Scientists Forces One of Their Own to Resign from Skeptic Group after Week: ‘Reminds Me of McCarthy’,” National Review Online, May 14, 2014
Anthony Watts, “In Climate Science, the More Things Change, the More They Stay the Same,” Watts Up With That?, May 17, 2014
Christopher Monckton of Brenchley, “Pseudoscientists’ Eight Climate Claims Debunked,” Watts Up With That?, May 17, 2014
John Hinderaker, “Why Global Warming Alarmism Isn’t Science,” PowerLine, May 17, 2014
Tom Sheahan, “The Specialized Meaning of Words in the “Antarctic Ice Shelf Collapse’ and Other Climate Alarm Stories,” Watts Up With That?, May 21, 2014
Anthony Watts, “Unsettled Science: New Study Challenges the Consensus on CO2 Regulation — Modeled CO2 Projections Exaggerated,” Watts Up With That?, May 22, 2014
Daniel B. Botkin, “Written Testimony to the House Subcommittee on Science, Space, and Technology,” May 29, 2014

Related posts:
The Limits of Science
The Thing about Science
Debunking “Scientific Objectivity”
Modeling Is Not Science
The Left and Its Delusions
Demystifying Science
AGW: The Death Knell
Modern Liberalism as Wishful Thinking
The Limits of Science (II)
The Pretence of Knowledge
“The Science Is Settled”

The Compleat Monty Hall Problem

Wherein your humble blogger gets to the bottom of the Monty Hall problem, sorts out the conflicting solutions, and declares that the standard solution is the right solution, but not to the Monty Hall problem as it’s usually posed.


The Monty Hall problem, first posed as a statistical puzzle in 1975, has been notorious since 1990, when Marilyn vos Savant wrote about it in Parade. Her solution to the problem, to which I will come, touched off a controversy that has yet to die down. But her solution is now widely accepted as the correct one; I refer to it here as the standard solution.

This is from the Wikipedia entry for the Monty Hall problem:

The Monty Hall problem is a brain teaser, in the form of a probability puzzle (Gruber, Krauss and others), loosely based on the American television game show Let’s Make a Deal and named after its original host, Monty Hall. The problem was originally posed in a letter by Steve Selvin to the American Statistician in 1975 (Selvin 1975a), (Selvin 1975b). It became famous as a question from a reader’s letter quoted in Marilyn vos Savant‘s “Ask Marilyn” column in Parade magazine in 1990 (vos Savant 1990a):

Suppose you’re on a game show, and you’re given the choice of three doors: Behind one door is a car; behind the others, goats. You pick a door, say No. 1, and the host, who knows what’s behind the doors, opens another door, say No. 3, which has a goat. He then says to you, “Do you want to pick door No. 2?” Is it to your advantage to switch your choice?

Here’s a complete statement of the problem:

1. A contestant sees three doors. Behind one of the doors is a valuable prize, which I’ll denote as $. Undesirable or worthless items are behind the other two doors; I’ll denote those items as x.

2. The contestant doesn’t know which door conceals $ and which doors conceal x.

3. The contestant chooses a door at random.

4. The host, who knows what’s behind each of the doors, opens one of the doors not chosen by the contestant.

5. The door chosen by the host may not conceal $; it must conceal an x. That is, the host always opens a door to reveal an x.

6. The host then asks the contestant if he wishes to stay with the door he chose initially (“stay”) or switch to the other unopened door (“switch”).

7. The contestant decides whether to stay or switch.

8. The host then opens the door finally chosen by the contestant.

9. If $ is revealed, the contestant wins; if x is revealed the contestant loses.

One solution (the standard solution) is to switch doors because there’s a 2/3 probability that $ is hidden behind the unopened door that the contestant didn’t choose initially. In vos Savant’s own words:

Yes; you [the contestant] should switch. The first [initially chosen] door has a 1/3 chance of winning, but the second [other unopened] door has a 2/3 chance.

The other solution (the alternative solution) is indifference. Those who propound this solution maintain that there’s a equal chance of finding $ behind either of the doors that remain unopened after the host has opened a door.

As it turns out, the standard solution doesn’t tell a contestant what to do in a particular game. But the standard solution does point to the right strategy for someone who plays or bets on a large number of games.

The alternative solution accurately captures the unpredictability of any particular game. But indifference is only a break-even strategy for a person who plays or bets on a large number of games.


The contestant may choose among three doors, and there are three possible ways of arranging the items behind the doors: S x x; x $ x; and x x $. The result is nine possible ways in which a game may unfold:

Equally likely outcomes

Events 1, 5, and 9 each have two branches. But those branches don’t count as separate events. They’re simply subsets of the same event; when the contestant chooses a door that hides $, the host must choose between the two doors that hide x, but he can’t open both of them. And his choice doesn’t affect the outcome of the event.

It’s evident that switching would pay off with a win in 2/3 of the possible events; whereas, staying with the original choice would off in only 1/3 of the possible events. The fractions 1/3 and 2/3 are usually referred to as probabilities: a 2/3 probability of winning $ by switching doors, as against a 1/3 probability of winning $ by staying with the initially chosen door.

Accordingly, proponents of the standard solution — who are now legion — advise the individual (theoretical) contestant to switch. The idea is that switching increases one’s chance (probability) of winning.


There are three problems with the standard solution:

1. It incorporates a subtle shift in perspective. The Monty Hall problem, as posed, asks what a contestant should do. The standard solution, on the other hand, represents the expected (long-run average) outcome of many events, that is, many plays of the game. For reasons I’ll come to, the outcome of a single game can’t be described by a probability.

2.  Lists of possibilities, such as those in the diagram above, fail to reflect the randomness inherent in real events.

3. Probabilities emerge from many repetitions of the kinds of events listed above. It is meaningless to ascribe a probability to a single event. In case of the Monty Hall problem, many repetitions of the game will yield probabilities approximating those given in the standard solution, but the outcome of each repetition will be unpredictable. It is therefore meaningless to say that a contestant has a 2/3 chance of winning a game if he switches. A 2/3 chance of winning refers to the expected outcome of many repetitions, where the contestant chooses to switch every time. To put it baldly: How does a person win 2/3 of a game? He either wins or doesn’t win.

Regarding points 2 and 3, I turn to Probability, Statistics and Truth (second revised English edition, 1957), by Richard von Mises:

The rational concept of probability, which is the only basis of probability calculus, applies only to problems in which either the same event repeats itself again and again, or a great number of uniform elements are involved at the same time. Using the language of physics, we may say that in order to apply toe theory of probability we must have a practically unlimited sequence of uniform observations. (p. 11)

*     *     *

In games of dice, the individual event is a single throw of the dice from the box and the attribute is the observation of the number of points shown by the dice. In the same of “heads or tails”, each toss of the coin is an individual event, and the side of the coin which is uppermost is the attribute. (p. 11)

*     *     *

We must now introduce a new term…. This term is “the collective”, and it denotes a sequence of uniform events or processes which differ by certain observable attributes…. All the throws of dice made in the course of a game [of many throws] from a collective wherein the attribute of the single event is the number of points thrown…. The definition of probability which we shall give is concerned with ‘the probability of encountering a single attribute [e.g., winning $ rather than x ] in a given collective [a series of attempts to win $ rather than x ]. (pp. 11-12)

*     *     *

[A] collective is a mass phenomenon or a repetitive event, or, simply, a long sequence of observations for which there are sufficient reasons to believe that the relative frequency of the observed attributed would tend to a fixed limit if the observations were indefinitely continued. The limit will be called the probability of the attribute considered within the collective [emphasis in the original]. (p. 15)

*     *     *

The result of each calculation … is always … nothing else but a probability, or, using our general definition, the relative frequency of a certain event in a sufficiently long (theoretically, infinitely long) sequence of observations. The theory of probability can never lead to a definite statement concerning a single event. The only question that it can answer is: what is to be expected in the course of a very long sequence of observations? It is important to note that this statement remains valid also if the calculated probability has one of the two extreme values 1 or 0 [emphasis added]. (p. 33)

To bring the point home, here are the results of 50 runs of the Monty Hall problem, where each result represents (i) a random initial choice between Door 1, Door 2, and Door 3; (ii) a random array of $, x, and x behind the three doors; (iii) the opening of a door (other than the one initially chosen) to reveal an x; and (iv) a decision, in every case, to switch from the initially chosen door to the other unopened door:

Results of 50 games

What’s relevant here isn’t the fraction of times that $ appears, which is 3/5 — slightly less than the theoretical value of 2/3.  Just look at the utter randomness of the results. The first three outcomes yield the “expected” ratio of two wins to one loss, though in the real game show the two winners and one loser would have been different persons. The same goes for any sequence, even the final — highly “improbable” (i.e., random) — string of nine straight wins (which would have accrued to nine different contestants). And who knows what would have happened in games 51, 52, etc.

If a person wants to win 2/3 of the time, he must find a game show that allows him to continue playing the game until he has reached his goal. As I’ve found in my simulations, it could take as many as 10, 20, 70, or 300 games before the cumulative fraction of wins per game converges on 2/3.

That’s what it means to win 2/3 of the time. It’s not possible to win a single game 2/3 of the time, which is the “logic” of the standard solution as it’s usually presented.


The alternative solution doesn’t offer a winning strategy. In this view of the Monty Hall problem, it doesn’t matter which unopened door a contestant chooses. In effect, the contestant is advised to flip a coin.

As discussed above, the outcome of any particular game is unpredictable, so a coin flip will do just as well as any other way of choosing a door. But randomly selecting an unopened door isn’t a good strategy for repeated plays of the game. Over the long run, random selection means winning about 1/2 of all games, as opposed to 2/3 for the “switch” strategy. (To see that the expected probability of winning through random selection approaches 1/2, return to the earlier diagram; there, you’ll see that $ occurs in 9/18 = 1/2 of the possible outcomes for “stay” and “switch” combined.)

Proponents of the alternative solution overlook the importance of the host’s selection of a door to open. His choice isn’t random. Therein lies the secret of the standard solution — as a long-run strategy.


It’s commonly said by proponents of the standard solution that when the host opens a door, he gives away information that the contestant can use to increase his chance of winning that game. One nonsensical version of this explanation goes like this:

  • There’s a 2/3 probability that $ is behind one of the two doors not chosen initially by the contestant.
  • When the host opens a door to reveal x, that 2/3 “collapses” onto the other door that wasn’t chosen initially. (Ooh … a “collapsing” probability. How exotic. Just like Schrödinger’s cat.)

Of course, the host’s action gives away nothing in the context of a single game, the outcome of which is unpredictable. The host’s action does help in the long run, if you’re in a position to play or bet on a large number of games. Here’s how:

  • The contestant’s initial choice (IC) will be wrong 2/3 of the time. That is, in 2/3 of a large number of games, the $ will be behind one of the other two doors.
  • Because of the rules of the game, the host must open one of those other two doors (HC1 and HC2); he can’t open IC.
  • When IC hides an x (which happens 2/3 of the time), either HC1 and HC2 must conceal the $; the one that doesn’t conceal the $ conceals an x.
  • The rules require the host to open the door that conceals an x.
  • Therefore, about 2/3 of the time the $ will be behind HC1 or HC2, and in those cases it will always be behind the door (HC1 or HC2) that the host doesn’t open.
  • It follows that the contestant, by consistently switching from IC to the remaining unopened door (HC1 or HC2), will win the $ about 2/3 of the time.

The host’s action transforms the probability — the long-run frequency — of choosing the winning door from 1/2 to 2/3. But it does so if and only if the player or bettor always switches from IC to HC1 or HC2 (whichever one remains unopened).

You can visualize the steps outlined above by looking at the earlier diagram of possible outcomes.

That’s all there is. There isn’t any more.

“The Science Is Settled”

Thales (c. 620 – c. 530 BC): The Earth rests on water.

Aneximenes (c. 540 – c. 475 BC): Everything is made of air.

Heraclitus (c. 540 – c. 450 BC): All is fire.

Empodecles (c. 493 – c. 435 BC): There are four elements: earth, air, fire, and water.

Democritus (c. 460 – c. 370 BC): Atoms (basic elements of nature) come in an infinite variety of shapes and sizes.

Aristotle (384 – 322 BC): Heavy objects must fall faster than light ones. The universe is a series of crystalline spheres that carry the sun, moon, planets, and stars around Earth.

Ptolemey (90 – 168 AD): Ditto the Earth-centric universe,  with a mathematical description.

Copernicus (1473 – 1543): The planets revolve around the sun in perfectly circular orbits.

Brahe (1546 – 1601): The planets revolve around the sun, but the sun and moon revolve around Earth.

Kepler (1573 – 1630): The planets revolve around the sun in elliptical orbits, and their trajectory is governed by magnetism.

Newton (1642 – 1727): The course of the planets around the sun is determined by gravity, which is a force that acts at a distance. Light consists of corpuscles; ordinary matter is made of larger corpuscles. Space and time are absolute and uniform.

Rutherford (1871 – 1937), Bohr (1885 – 1962), and others: The atom has a center (nucleus), which consists of two elemental particles, the neutron and proton.

Einstein (1879 – 1955): The universe is neither expanding nor shrinking.

That’s just a small fraction of the mistaken and incomplete theories that have held sway in the field of physics. There are many more such mistakes and lacunae in the other natural sciences: biology, chemistry, and earth science — each of which, like physics, has many branches. And in all branches there are many unresolved questions. For example, the Standard Model of particle physics, despite its complexity, is known to be incomplete. And it is thought (by some) to be unduly complex; that is, there may be a simpler underlying structure waiting to be discovered.

Given all of this, it is grossly presumptive to claim that climate science is “settled” when the phenomena that it encompasses are so varied, complex, often poorly understood, and often given short shrift (e.g., the effects of solar radiation on the intensity of cosmic radiation reaching Earth, which affects low-level cloud formation, which affects atmospheric temperature and precipitation).

Anyone who says that climate science is “settled” is either ignorant, stupid, or a freighted with a political agenda.

The Pretence of Knowledge

Friedrich Hayek, in his Nobel Prize lecture of 1974, “The Pretence of Knowledge,” observes that

the great and rapid advance of the physical sciences took place in fields where it proved that explanation and prediction could be based on laws which accounted for the observed phenomena as functions of comparatively few variables.

Hayek’s particular target was the scientism then (and still) rampant in economics. In particular, there was (and is) a quasi-religious belief in the power of central planning (e.g., regulation, “stimulus” spending, control of the money supply) to attain outcomes superior to those that free markets would yield.

But, as Hayek says in closing,

There is danger in the exuberant feeling of ever growing power which the advance of the physical sciences has engendered and which tempts man to try, “dizzy with success” … to subject not only our natural but also our human environment to the control of a human will. The recognition of the insuperable limits to his knowledge ought indeed to teach the student of society a lesson of humility which should guard him against becoming an accomplice in men’s fatal striving to control society – a striving which makes him not only a tyrant over his fellows, but which may well make him the destroyer of a civilization which no brain has designed but which has grown from the free efforts of millions of individuals.

I was reminded of Hayek’s observations by John Cochrane’s post, “Groundhog Day” (The Grumpy Economist, May 11, 2014), wherein Cochrane presents this graph:

The fed's forecasting models are broken

Cochrane adds:

Every serious forecast looked like this — Fed, yes, but also CBO, private forecasters, and the term structure of forward rates. Everyone has expected bounce-back growth and rise in interest rates to start next year, for the last 6 years. And every year it has not happened. Welcome to the slump. Every year, Sonny and Cher wake us up, and it’s still cold, and it’s still grey. But we keep expecting spring tomorrow.

Whether the corrosive effects of government microeconomic and regulatory policy, or a failure of those (unprintable adjectives) Republicans to just vote enough wasted-spending Keynesian stimulus, or a failure of the Fed to buy another $3 trillion of bonds, the question of the day really should be why we have this slump — which, let us be honest, no serious forecaster expected.

(I add the “serious forecaster” qualification on purpose. I don’t want to hear randomly mined quotes from bloviating prognosticators who got lucky once, and don’t offer a methodology or a track record for their forecasts.)

The Fed’s forecasting models are nothing more than sophisticated charlatanism — a term that Hayek applied to pseudo-scientific endeavors like macroeconomic modeling. Nor is charlatanism confined to economics and the other social “sciences.” It’s rampant in climate “science,” as Roy Spencer has shown. Consider, for example, this graph from Spencers’s post, “95% of Climate Models Agree: The Observations Must Be Wrong” (Roy Spencer, Ph.D., February 7, 2014):

95% of climate models agree_the observations must be wrong

Spencer has a lot more to say about the pseudo-scientific aspects of climate “science.” This example is from “Top Ten Good Skeptical Arguments” (May 1, 2014):

1) No Recent Warming. If global warming science is so “settled”, why did global warming stop over 15 years ago (in most temperature datasets), contrary to all “consensus” predictions?

2) Natural or Manmade? If we don’t know how much of the warming in the longer term (say last 50 years) is natural, then how can we know how much is manmade?

3) IPCC Politics and Beliefs. Why does it take a political body (the IPCC) to tell us what scientists “believe”? And when did scientists’ “beliefs” translate into proof? And when was scientific truth determined by a vote…especially when those allowed to vote are from the Global Warming Believers Party?

4) Climate Models Can’t Even Hindcast How did climate modelers, who already knew the answer, still fail to explain the lack of a significant temperature rise over the last 30+ years? In other words, how to you botch a hindcast?

5) …But We Should Believe Model Forecasts? Why should we believe model predictions of the future, when they can’t even explain the past?

6) Modelers Lie About Their “Physics”. Why do modelers insist their models are based upon established physics, but then hide the fact that the strong warming their models produce is actually based upon very uncertain “fudge factor” tuning?

7) Is Warming Even Bad? Who decided that a small amount of warming is necessarily a bad thing?

8) Is CO2 Bad? How did carbon dioxide, necessary for life on Earth and only 4 parts in 10,000 of our atmosphere, get rebranded as some sort of dangerous gas?

9) Do We Look that Stupid? How do scientists expect to be taken seriously when their “theory” is supported by both floods AND droughts? Too much snow AND too little snow?

10) Selective Pseudo-Explanations. How can scientists claim that the Medieval Warm Period (which lasted hundreds of years), was just a regional fluke…yet claim the single-summer (2003) heat wave in Europe had global significance?

11) (Spinal Tap bonus) Just How Warm is it, Really? Why is it that every subsequent modification/adjustment to the global thermometer data leads to even more warming? What are the chances of that? Either a warmer-still present, or cooling down the past, both of which produce a greater warming trend over time. And none of the adjustments take out a gradual urban heat island (UHI) warming around thermometer sites, which likely exists at virtually all of them — because no one yet knows a good way to do that.

It is no coincidence that leftists believe in the efficacy of central planning and cling tenaciously to a belief in catastrophic anthropogenic global warming. The latter justifies the former, of course. And both beliefs exemplify the left’s penchant for magical thinking, about which I’ve written several times (e.g., here, here, here, here, and here).

Magical thinking is the pretense of knowledge in the nth degree. It conjures “knowledge” from ignorance and hope. And no one better exemplifies magical thinking than our hopey-changey president.

*     *     *

Related posts:
Modeling Is Not Science
The Left and Its Delusions
Economics: A Survey
AGW: The Death Knell
The Keynesian Multiplier: Phony Math
Modern Liberalism as Wishful Thinking

Not Over the Hill

The Washington Post reports on some research about intelligence that is as irrelevant as the candle problem. Specifically:

[R]esearchers at Canada’s Simon Fraser University … have found that measurable declines in cognitive performance begin to occur at age 24. In terms of brainpower, you’re over the hill by your mid-20s.

The researchers measured this by studying the performance of thousands of players of Starcraft 2, a strategy video game….

Even worse news for those of us who are cognitively over-the-hill: the researchers find “no evidence that this decline can be attenuated by expertise.” Yes, we get wiser as we get older. But wisdom doesn’t substitute for speed. At best, older players can only hope to compensate “by employing simpler strategies and using the game’s interface more efficiently than younger players,” the authors say.

So there you have it: scientific evidence that we cognitively peak at age 24. At that point, you should probably abandon any pretense of optimism and accept that your life, henceforth, will be a steady descent into mediocrity, punctuated only by the bitter memories of the once seemingly-endless potential that you so foolishly squandered in your youth. Considering that the average American lives to be 80, you’ll have well over 50 years to do so! (Christopher Ingraham, “Your Brain Is Over the Hill by Age 24,” April 16, 2014)

Happily, Starcraft 2 is far from a representation of the real world. Take science, for example. I went to Wikipedia and obtained the list of all Nobel laureates in physics. It’s a long list, so I sampled it — taking the winners for the first five years (1901-1905), the middle five years (1955-1959) and the most recent five years (2009-2013). Here’s a list of the winners for those 15 years, and the approximate age of each winner at the time he or she did the work for which the prize was awarded:

1901 Wilhelm Röntgen (50)

1902 Hendrik Lorentz; (43) and Pieter Zeeman (31)

1903 Henri Becquerel, (44), Pierre Curie (37), and Marie Curie (29)

1904 Lord Rayleigh (52)

1955 Willis Lamb (34) and Polykarp Kusch (40)

1956 John Bardeen (39), Walter Houser Brattain (45), and William Shockley (37)

1957 Chen Ning Yang (27) and Tsung-Dao Lee (23)

1958 Pavel Cherenkov (30), Ilya Frank (26), and Igor Tamm (39)

1959 Emilio G. Segrè (50) and Owen Chamberlain (35)

2009 Charles K. Kao (33), Willard S. Boyle (45), and George E. Smith (39)

2010 Andre Geim (46) and Konstantin Novoselov (34)

2011 Saul Perlmutter (39), Adam G. Riess (29), and Brian Schmidt (31)

2012 Serge Haroche (40-50) and David J. Wineland (40-50)

2013 François Englert (32) and Peter W. Higgs (35)

There’s exactly one person within a year of age 24 (Tsung-Dao Lee, 23), and a few others who were still in their (late) 20s. Most of the winners were in their 30s and 40s when they accomplished their prize-worthy scientific feats. And there are at least as many winners who were in their 50s as winners who were in their 20s.

Let’s turn to so-called physical pursuits, which often combine brainpower (anticipation, tactical improvisation, hand-eye coordination) and pure physical skill (strength and speed). Baseball exemplifies such a pursuit. Do ballplayers go sharply downhill after the age of 24? Hardly. On average, they’re just entering their best years at age 24, and they perform at peak level for several years.

I’ll use two charts to illustrate the point about ballplayers. The first depicts normalized batting average vs. age for 86 of the leading hitters in the history of the American League*:

Greatest hitters_BA by age_86 hitters

Because of the complexity of the spreadsheet from which the numbers are taken, I was unable to derive a curve depicting mean batting average vs. age. But the density of the plot lines suggests that the peak age for batting average begins at 24 and extends into the early 30s. Further, with relatively few exceptions, batting performance doesn’t decline sharply until the late 30s.

Among a more select group of players, and by a different measure of performance, the peak years occur at ages 24-28, with a slow decline after 28**:

Offensive average by age_25 leading hitters

The two graphs suggest to me that ballplayers readily compensate for physical decline (such as it is) by applying the knowledge they acquire in the course of playing the game. Such knowledge would include “reading” pitchers to make better guesses about the pitch that’s coming, knowing where to hit a ball in a certain ballpark against certain fielders, judging the right moment to attempt a stolen base against a certain pitcher-catcher combination, hitting to the opposite field on occasion instead of trying to pull the ball every time, and so on.

I strongly suspect that what is true in baseball is true in many walks of life: Wisdom — knowledge culled from experience — compensates for pure brainpower, and continues to do so for a long time. The Framers of the Constitution, who weren’t perfect but who were astute observers of the human condition, knew as much. That’s why they set 35 as the minimum age for election to the presidency. (Subsequent history — notably, the presidencies of TR, JFK, Clinton, and Obama — tells us that the Framers should have made it 50.)

I do grow weary of pseudo-scientific crap like the research reported in the Post. But it does give me something to write about. And most of the pseudo-science is harmless, unlike the statistical lies on which global-warming hysteria is based.

* The numbers are drawn from the analysis described in detail here and here, which is based on statistics derived through the Play Index at The bright red line represents Ty Cobb’s career, which deserves special mention because of Cobb’s unparalleled dominance as a hitter-for-average over a 24-year career, and especially for ages 22-32. I should add that Cobb’s dominance has been cemented by Ichiro Suzuki’s sub-par performance in the three seasons since I posted this, wherein I proclaimed Cobb the American League’s best all-time hitter for average, taking age into account. (There’s no reason to think that the National League has ever hosted Cobb’s equal.)

** This is an index, where 100 represents parity with the league average. I chose the 25 players represented here from a list of career leaders in OPS+ (on-base percentage plus slugging average, normalized for league averages and park factors). Because of significant changes in rules and equipment in the late 1800s and early years of the 1900s (see here, here, and here), players whose careers began before 1907 were eliminated, excepting Cobb, who didn’t become a regular player until 1906. Also eliminated were Barry Bonds and Mark McGwire, whose drug-fueled records don’t merit recognition, and Joey Votto, who has completed only eight seasons. Offensive Average (OA) avoids the double-counting inherent in OPS+, which also (illogically) sums two fractions with different denominators. OA measures a player’s total offensive contribution (TOC) per plate appearance (PA) in a season, normalized by the league average for that season. TOC = singles + doubles x 2 + triples x 3 + home runs x 4 + stolen bases – times caught stealing + walks – times grounded into a double play + sacrifice hits + sacrifice flies. In the graph, Cobb seems to disappear into the (elite) crowd after age 24, but that’s an artifact of Cobb’s preferred approach to the game — slapping hits and getting on base — not his ability to hit the long ball, for which extra credit is given in computing OA. (See this, for example.)