The Great Debate

General Ability and Specific Abilities in the Prediction of Important Outcomes

Edited by
July 2019
108 pages
  • ISBN978-3-03921-167-8 (Paperback)
  • ISBN978-3-03921-168-5 (PDF)

This book is a reprint of the Special Issue The Great Debate: General Ability and Specific Abilities in the Prediction of Important Outcomes that was published in

Biology & Life Sciences
Computer Science & Mathematics
Social Sciences, Arts & Humanities
Public Health & Healthcare

There are many different theories of intelligence. Although these theories differ in their nuances, nearly all agree that there are multiple cognitive abilities and that they differ in the breadth of content they are typically associated with. There is much less agreement about the relative importance of cognitive abilities of differing generality for predicting important real-world outcomes, such as educational achievement, career success, job performance, and health. Some investigators believe that narrower abilities hold little predictive power once general abilities have been accounted for. Other investigators contend that specific abilities are often as—or even more—effective in forecasting many practical variables as general abilities. These disagreements often turn on differences of theory and methodology that are both subtle and complex. The five cutting-edge contributions in this volume, both empirical and theoretical, advance the conversation in this vigorous, and highly important, scientific debate.

  • Paperback
License and Copyright
© 2019 by the authors; CC BY-NC-ND license
general cognitive ability; specific cognitive abilities; academic achievement; job performance; occupational attainment; health; longevity; situational specificity; bifactor model; cognitive abilities; educational attainment; general mental ability; hierarchical factor model; higher-order factor model; intelligence; job performance; nested-factors model; relative importance analysis; specific abilities; specific ability; second stratum abilities; academic performance; nested-factor models; relative importance analysis; predictor-criterion bandwidth alignment; g-factor; specific abilities; scholastic performance; school grades; machine learning; curvilinear relations; ability differentiation; bifactor model; identification; bifactor(S-1) model; general factor; specific factors; general intelligence (g); non-g factors; specific abilities; ability tilt; non-g residuals; cognitive abilities; specific abilities; general abilities; general mental ability; relative importance; narrow abilities; subscores; intelligence; cognitive tests

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