Advertisement

Of Genes and IQ

  • Michael Daniels
  • Bernie Devlin
  • Kathryn Roeder

Abstract

The fundamental premise of Herrnstein and Murray’s opus, The Bell Curve, is that intelligence and its proxy IQ are determined primarily by genes.1 Economic and social success, according to their analyses, are determined primarily by IQ. Thus logic dictates that economic and social success are due largely to genes, which therefore explains why government interventions to improve the lot of the poor have been on the whole unsuccessful. In one eloquent volume, the authors serve up justification for that oft-heard refrain “the poor will always be poor.”

Keywords

Maternal Effect Assortative Mating Additive Genetic Variance Bell Curve Social Success 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Herrnstein, R J. and Murray, C. (1994) The Bell Curve: Intelligence and Class Structure in American Life, The Free Press, New York.Google Scholar
  2. 2.
    Bouchard, T.J., Jr., and McGue, M. (1981), “Familial Studies of Intelligence: A Review,” Science, 212, 1055–1059.CrossRefGoogle Scholar
  3. 3.
    Fisher, R.A. (1918), “The Correlation Among Relatives on the Supposition of Mendelian Inheritance,” Transactions of the Royal Society, Edinburgh, 52, 399–433.Google Scholar
  4. 4.
    Fisher, R.A. (1951), “Limits to Intensive Production in Animals,” British Agricultural Bulletin, 4, 217–218.Google Scholar
  5. 5.
    Falconer, D.S. (1981), Introduction to Quantitative Genetics,Longman, New York.Google Scholar
  6. 6.
    Devlin, B., Roeder, K., and Daniels, M. (1997), “On the Heritability of IQ,” Nature, in press.Google Scholar
  7. 7.
    Bouchard, TJ., Jr., personal communication.Google Scholar
  8. 8.
    Bouchard, T.J., Jr., Lykken, D.T., McGue, M., Segal, N.L., and Tellegen, A. (1990), “Sources of Human Psychological Differences: The Minnesota Study of Twins Reared Apart,” Science, 250, 223–228.CrossRefGoogle Scholar
  9. 9.
    Pedersen, N.L., Plomin, R., Nesselroade, J.R., and McClearn, G.E., (1992), “A Quantitative Genetic Analysis of Cognitive Abilities During the Second Half of the Life Span,” Psychological Science 3, 346–353.CrossRefGoogle Scholar
  10. 10.
    ’McGue, M., Bouchard, T.J., Jr., Iacono, W.G., and Lykken, D.T. (1993) “Behavioral Genetics of Cognitive Ability: A Life-Span Perspective,” in Nature, Nurture, and Psychology (eds. Plomin, R., and McClean, G.E.), American Psychological Association, Washington, D.C., pp. 59–76.Google Scholar
  11. 11.
    Rosenthal, R. (1984), Meta-Analytic Procedures fir Social Research, Sage Publications, Beverly Hills, CA. National Research Council (NRC) (1992), Combining Information. Statistical Issues and Opportunitiesfor Research. National Academy Press, Washington, D.C.Google Scholar
  12. 12.
    Chipuer, H.M., Rovine, M J., and Plomin, R. (1990), “LISREL Modeling: Genetic and Environmental Influences on IQ Revisited,” Intelligence, 14, 11–29.CrossRefGoogle Scholar
  13. 13.
    Rao, D.C., Morton, N.E., Lalouel, J.M., and Lew, R. (1982), “Path Analysis Under Generalized Assortative Mating. II. American IQ,” Genetical Research (Camb.), 39, 187–198.CrossRefGoogle Scholar
  14. 14.
    Plomin, R., and Loehlin, J.C. (1989), “Direct and Indirect IQ Heritability Studies: A Puzzle,” Behavior Genetics,19, 332–342Google Scholar
  15. 15.
    Fisher, R.A. (1958), The Genetical Theory ofNatural Selection, second revised edition, Dover Publications, Inc. New York.Google Scholar
  16. 16.
    Sattler, J. (1988), Assessment of Children’s Intelligence and Other Special Abilities, Allyn and Bacon, Boston.Google Scholar
  17. 17.
    Ree, M J. and Earles, J.A. (1991), Aptitude of Future Manpower: Consequences of Demographic Change, Brooks Airforce Base: Manpower and Personnel Division, Air Force Systems Command.Google Scholar
  18. 18.
    Flynn, J.R. (1987), “Massive IQ Gains in 14 Nations: What Do IQ Tests Really Measure?,” Psychological Bulletin, 101, 171–191.CrossRefGoogle Scholar
  19. 19.
    Muller HJ. (1962), Studies in Genetics. Indiana University Press, Bloomington, IN.Google Scholar
  20. 20.
    Scarr, S. Pakstis, A.J., Katz, S.H., and Barker, W.B. (1977), “Absence of a Relationship Between Degree of White Ancestry and Intellectual Skills Within a Black Population,” Human Genetics, 39, 69–86.CrossRefGoogle Scholar
  21. 21.
    Loehlin, J.C., Vanderburg, S.G., and Osborne, R.T. (1973), “Blood Group Genes and Negro-White Ability Differences,” Behavior Genetics, 3, 263–270. Tizard, B. (1974), “I.Q. and Race,” Nature, 247,316. Google Scholar
  22. 22.
    . MacLean, C., Adams, M.S., Leyshon, W.C., Workman, P.L., Reed, T.E., Gershowitz, H., and Weitkamp, L.R. (1974), “Genetic Studies on Hybrid Populations. III. Blood Pressure in the American Black Community,”American Journal ofHuman Genetics, 26, 614–626.Google Scholar
  23. 23.
    Wall Street Journal, December 13, 1994, p. A,8.Google Scholar
  24. 24.
    Fisher, R.A. (1920, “On the ‘Probable Error’ on a Coefficient of Correlation Deduced from a Small Sample,” Metron, 1; 3–32.Google Scholar
  25. 25.
    Geyer, G. (1989), “Practical Markov Chain Monte Carlo,” Statistical Science 4, 473¡ª 482. Smith, A.F.M., and Roberts, G.O. (1993) “Bayesian Computation via the Gibbs Sampler and Related Markov Chain Monte Carlo Methods,” Journal of the Royal Statistical Society B, 55, 3–24 . Google Scholar
  26. 26.
    Verdinelli, I., and Wasserman, L. (1995) “Computing Bayes Factors By Using a Generalization of the Savage-Dickey Density Ratio,” Journal of the American Statistical Association, 90, 614–618.MathSciNetzbMATHCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 1997

Authors and Affiliations

  • Michael Daniels
  • Bernie Devlin
  • Kathryn Roeder

There are no affiliations available

Personalised recommendations