Thirty years of research on race differences in cognitive ability.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The culture-only (0 % genetic–100 % environmental) and the hereditarian (50% genetic–50 % environmental) models of the causes of mean Black–White differences in cognitive ability are compared and contrasted across 10 categories of evidence: the worldwide distribution of test scores, g factor of mental ability, heritability, brain size and cognitive ability, transracial adoption, racial admixture, regression, related life-history traits, human origins research, and hypothesized environmental variables. The new evidence reviewed here points to some genetic component in Black–White differences in mean IQ. The implication for public policy is that the discrimination model (i.e., Black–White differences in socially valued outcomes will be equal barring discrimination) must be tempered by a distributional model (i.e., Black–White outcomes reflect underlying group characteristics). Section 1: Background Throughout the history of psychology, no question has been so persistent or so resistant to resolution as that of the relative roles of nature and nurture in causing individual and group differences in cognitive ability (Degler, 1991;
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it