Studying Correlations between Genetic Variation and Test Score Gaps

Edited By: Gregory Connor, John G.R. Fuerst

£74.99

This book presents exciting findings on the sources of test score gaps, using powerful DNA-based methods to analyze race, socio-economic status, and ancestry. It also considers the policy question of how these findings should be disseminated to the public.

This book is an edited collection of recently published papers on the sources of average test score gaps when analysed through the lenses of race…

This book is an edited collection of recently published papers on the sources of average test score gaps when analysed through the lenses of race and ethnicity, socio-economic status, and biogeographic ancestries such as European, African, and East Asian ancestry. It brings together exciting recent findings that rely on powerful DNA-based methods developed in the last few decades. The book also considers the public policy question as to whether, and how, these findings should be disseminated to the general public audience.

Gregory Connor recently retired from his position as Professor of Finance at Maynooth University (Ireland). He previously taught at the London School of Economics (UK), the University of California-Berkeley (USA), and Northwestern University (USA). He has published widely and is co-author (with Robert Korajczyk and Lisa Goldberg) of Financial Risk Analysis. His research focusses on factor modelling with large cross-sections applied to macro-finance, genome-wide association studies (GWAS), the g-factor, and gene/environment analysis of variance (ANOVA).

John Fuerst has previously conducted research at Cleveland State University (USA), North Carolina State University (USA), and Case Western Reserve University (USA). He is currently enrolled in a post graduate programme in bioinformatics and has previously done graduate work in psychology. His research focusses on behavioural genetics, psychometrics, genome-wide association studies (GWAS), and differential psychology.

Gregory Connor, John G.R. Fuerst, Nathan Cofnas, Noah Carl, Russell Warne, Emil Kirkegaard, Robert Williams, Gerhard Meisenberg, Jordan Lasker, Bryan Pesta, Davide Piffer, Meng Hu, Vladimir Shibaev

Paperback

ISBN: 1-5275-7566-7
ISBN13: 978-1-5275-7566-0
Date of Publication: 2024-02-15

Ebook

ISBN: 1-5275-7567-5
ISBN13: 978-1-5275-7567-7
Date of Publication: 2024-02-15

Categories: Social Sciences, Education, Education, Developmental and Educational Psychology

Pages: 359

Subject Codes:

BIC: JN, JNC
THEMA: JN, JNC

Pages: 359

"If you are a quantitative social scientist, you have a responsibility to wrestle with the material in this book. It is important that you do it partly because the genetics of differences in test scores is of the utmost relevance to a wide range of topics involving both scholarly issues and public policy. There is also a larger reason. It is important that you treat its arguments as legitimate scientific inquiry to help rescue social science from the dark age of censorship and ideological orthodoxy into which it has fallen."
- Charles Murray F.A. Hayek Emeritus Scholar at the American Enterprise Institute, and co-author (with Richard Herrnstein) of The Bell Curve.
"This anthology provides an excellent overview of the research on test score gaps and their empirical relationship with and possible theoretical explanation through genetic factors. Widely scattered individual works are brought together in one volume and presented with an introductory text that is understandable to a broader public. A must-read for everyone interested in the topic and especially for those who are initially skeptical about this research but want to get to know it better for a fruitful scientific discussion."
- Dr Heiner Rindermannn Professor of Educational and Developmental Psychology at Chemnitz University of Technology, Germany, and author of Cognitive Capitalism: Human Capital and the Wellbeing of Nations

Studying Correlations between Genetic Variation and Test Score Gaps

Paperback

Ebook

Subject Codes:

Recommended