Why mainstream research will not end scientific racism in psychology
Bibliographic record
Abstract
Mainstream research on racial essentialization may be valuable in the fight against racism, as Held (2020) suggested. I argue that the production of scientific racism in the literature of psychology is unlikely to be affected by such research. Assertions by psychologists of Black people’s average inferiority in brain size, intelligence, and morality have persisted for over 100 years despite repeated, careful critiques. Recent presentations of these old and discredited claims have sidestepped the fundamental criticism that they rest on essentialized racial categories. The survival of scientific racism in mainstream psychology journals should be understood as a community project with its own Weltanschauung of “racial progress.”
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.072 | 0.091 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.085 |
| Scholarly communication | 0.013 | 0.026 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.016 | 0.027 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".