The G Factor: The Science of Mental Ability

By Arthur R. Jensen | Go to book overview

All of the MVT procedures and variables were the same as in the study of blacks and whites.

All of the RT and RTSD variables had highly significant correlations with the SPM (average r = -.25, p < .001); none of the MT and MTSD variables was significantly correlated with the SPM (mean r = +.01). On RT and RTSD, the overall standardized mean white-Chinese difference was 0.34σ, about the same as the 0.32σ difference they showed on Raven's SPM. (The actual overall mean RT for the whites was 1,480 msec; for the Chinese, 1,204 msec.) But note: The overall average white-Chinese difference on MT and MTSD was in the opposite direction, -0.19σ.

When the vector of the twelve MVT variables' g loadings was correlated with the vector of the white-Chinese standardized mean differences on each of the MVT variables, the Pearson r = -.93 and the rank order rs = -.90 (p < .01). This indicates that the larger the MVT variable's estimated g loading (i.e., its correlation with the SPM), the more the Chinese outperform the whites on the MVT. On this test, the whites compared with the Chinese in much the same way that the blacks compared with the whites in the previous study. It should be noted that these Chinese children were mostly of lower SES than the white children. The three racial groups--Chinese, white, and black--score in the same rank order both on the SPM and on untimed paper-and-pencil tests of mathematical problem solving.

Conclusion. What these ECT studies clearly demonstrate regarding the group difference on mental tests is that Spearman's hypothesis applies not only to conventional psychometric tests (as proved in many studies using such tests), but also to a quite different type of mental measurement, namely chronometric variables derived from tasks that involve the most elemental aspects of information processing (such as speed and consistency of stimulus apprehension, choice decision, discrimination, and retrieval of information stored in LTM). As shown in many other studies, individual differences in these chronometric variables are correlated to varying degrees with psychometric g. The fact that the relative sizes of these correlations are directly related to the variable sizes of the standardized mean black-white or Chinese-white differences on the chronometric variables means that such differences on conventional g-loaded tests are not solely attributable to one group's advantage in the specific information content of LTM, or to strategies of reasoning and problem solving, or to other metaprocesses of the kind presumably involved in complex mental tests.


NOTES
1.
The book edited by Jaynes & Williams ( 1989) provides comprehensive demographic information and statistics on the social and economic conditions of blacks in America.
2.
Entrée to virtually the whole literature on race and IQ, including the descriptive statistics of IQ (and other mental tests) in blacks and whites is accessible through the following key references: Eysenck ( 1984b), Herrnstein & Murray ( 1994), Jensen ( 1973),

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The G Factor: The Science of Mental Ability
Table of contents

Table of contents

  • Title Page iii
  • Contents vii
  • Preface ix
  • Acknowledgments xiii
  • Chapter 2 - The Discovery of G 18
  • Notes 39
  • Chapter 3 - The Trouble with "Intelligence" 45
  • Notes 68
  • Chapter 4 - Models and Characteristics of G 95
  • Chapter 5 - Challenges to G 105
  • Notes 133
  • Chapter 6 - Biological Correlates of G 137
  • Notes 165
  • Chapter 7 - The Heritability of G 169
  • Notes 197
  • Chapter 8 - Information Processing and G 203
  • Notes 261
  • Chapter 9 - The Practical Validity of G 270
  • Notes 301
  • Chapter 10 - Construct, Vehicles, and Measurements 306
  • Notes 344
  • Chapter 11 - Population Differences in G 350
  • Notes 402
  • Chapter 12 - Population Differences in G: Causal Hypotheses 418
  • Notes 516
  • Chapter 13 - Sex Differences in G 531
  • Notes 542
  • Chapter 14 - The G Nexus 544
  • Notes 579
  • Appendix A - Spearman's "Law of Diminishing Returns" 585
  • Appendix B - Method of Correlated Vectors 589
  • Appendix C - Multivariate Analyses of a Nexus 593
  • References 597
  • Name Index 635
  • Subject Index 643
  • About the Author 649
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