Intelligence, Genes, and Success: Scientists Respond to The Bell Curve (Statistics for Social Science and Public Policy) [Paperback] Devlin, Bernie; Fienberg, Stephen E.; Resnick, Daniel P. and Roeder, Kathryn

This is author-approved bcc. If it is too long, delete the last sentence in each of the biographies. THE BELL CURVE by Richard Herrnstein and Charles Murray, a best selling book published in 1994, set off a hailstorm of controversy about the relationships among IQ, genetics, and various social outcomes, including welfare dependency, crime, and earnings. Much of the public reaction to the book was polemical and did not focus on the details of the science and in particular on the validity of the statistical arguments that underlie the books's conclusions. A detailed understanding of the arguments in THE BELL CURVE requires knowledge about (i) statistical models for genetic heritability, (ii) factor analysis, especially as it has been applied to the analysis of IQ tests, (iii) logistic regression and multiple regression analyses,and (iv) causal modelling and alternative statistical frameworks for making inference from longitudinal data. In this volume a group of statisticians and social scientists have assembled a scientific response to THE BELL CURVE. The sixteen chapters begin by presenting an overview of the scientific and statistical issues and summarize the material in Herrnstein and Murray's book. Then separate chapters by various experts deal with more focused issues, including reanalyses of data relied upon by the authors of THE BELL CURVE. The final chapters consider some of the implications of the work described in the book for American public policy and scientific research. BERNIE DEVLIN is Program Director of the Computational Genetics Program at the University of Pittsburgh Medical Center. He serves on

I Overview.- 1 Reexamining The Bell Curve.- The Bell Curve’sArgument.- The History of the Argument.- Our Response to The Bell Curve.- 2 A Synopsis of The Bell Curve.- The Emergence of a Cognitive Elite.- Cognitive Classes and Social Behavior.- The National Context.- Living Together.- II The Genetics—Intelligence Link.- 3 Of Genes and IQ.- Inheritance versus Heritability.- Estimating the Heritability of IQ.- Social Implications.- Epilogue.- Appendix: Model for Bayesian Meta-Analysis of IQ Studies.- 4 The Malleability of Intelligence Is Not Constrained by Heritability.- Heritability.- Heritability and Plasticity.- Plasticity of Intelligence.- Heritability as Impediment.- 5 Racial and Ethnic Inequalities in Health: Environmental, Psychosocial, and Physiological Pathways.- Black/White Differences in Morbidity and Mortality.- Racial/Ethnic Differences in Infectious Disease: The Case of Tuberculosis.- A Life-History Approach to Health Outcomes: The Wisconsin Longitudinal Study.- Physiological Substrates: The Character of the Current Knowledge Base.- Discussion.- III Intelligence and the Measurement of IQ.- 6 Theoretical and Technical Issues in Identifying a Factor of General Intelligence.- Is There a g? A Brief History.- Concrete Example of a Factorial Dataset.- Exploratory Factor Analysis of the Sample Dataset.- Confirmatory Factor Analysis of the Sample Dataset.- Justifying a General Factor.- Evidence from Selected Datasets.- The Holzinger and Swineford Dataset.- The Hakstian and Cattell Dataset.- The Wothke et al. Dataset.- Conclusions and Final Comment.- 7 The Concept and Utility of Intelligence.- A Very Brief History of Intelligence Tests.- What Is Intelligence? The Psychometric Evidence.- The Revisionist Position: An Alternative Approach to Intelligence.- Implications for Public Policy.- IV Intelligence and Success: Reanalyses of Data from the NLSY.- 8 Cognitive Ability, Wages, and Meritocracy.- Is Ability Unidimensional?.- The Wage Premium for Ability.- Conclusions.- 9 The Hidden Gender Restriction: The Need for Proper Controls When Testing for Racial Discrimination.- Earnings Analysis inThe Bell Curve.- Controlling for Gender: Testing Implied Restrictions.- Detecting Discrimination.- A Standard Wage Function.- The Racial Wage Gap in the Standard Wage Function.- Conclusions.- 10 Does Staying in School Make You Smarter? The Effect of Education on IQ in The Bell Curve.- Methods and Data.- Previous Research.- Reanalysis of the Herrnstein—Murray Model.- Conclusions.- 11 Cognitive Ability, Environmental Factors, and Crime: Predicting Frequent Criminal Activity.- Method.- Variables.- Logit Model: Interpretation.- Logit Model: Evaluation.- Conclusions.- 12 Social Statistics and Genuine Inquiry: Reflections on The Bell Curve.- Varieties of Pseudo-Science.- The Aims of Inquiry.- Reliability and Social Theory.- Algorithmic Social Science.- Factor Analysis and The Bell Curve.- Regression andThe Bell Curve.- Scientific Search.- Conclusions.- V The Bell Curve and Public Policy.- 13 A “Head Start” in What Pursuit? IQ Versus Social Competence as the Objective of Early Intervention.- The Nation Declares War on Poverty.- The Environmental Mystique.- Evaluations of Cognitive Benefits.- The Broader Picture.- Attempts to Measure Social Competence.- Improving Programs for At-Risk Children.- 14 Is There a Cognitive Elite in America?.- The Evil Elite.- Origin of Species.- Who Is Really Elite?.- 15 Science, Public Policy, and The Bell Curve.- Science: The Genetics—Intelligence Link.- Science: Intelligence and the Measurement of IQ.- Science: Analyzing the Outcomes Data.- Genetics, Race, and IQ.- Public Policy.- Conclusions.- Contributor Biographies.- Author Index.