Processes in Racial Discrimination: Differential Weighting of Conflicting Information
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 present research explored how White college students may exhibit response patterns associated with a subtle and rationalizable contemporary bias, aversive racism. In the study, higher and lower prejudice-scoring participants evaluated applicants for admission to their university, for whom information about high school achievement and college board scores (aptitude and achievement test scores) was independently varied as strong or weak. As predicted, discrimination against Black applicants relative to White applicants did not occur when the credentials were consistently strong or weak; however, discrimination by relatively high prejudice-scoring participants did emerge when the credentials were mixed and hence ambiguous. Moreover, relatively high prejudice-scoring participants weighed the different, conflicting criteria in ways that could justify or rationalize discrimination against Black applicants. The implications of these data for understanding contemporary racism and their relation to the shifting standards model of bias are considered.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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