Intersecting race and gender stereotypes: Implications for group-level attitudes
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
Two studies examined the relationship between explicit stereotyping and prejudice by investigating how stereotyping of minority men and women may be differentially related to prejudice. Based on research and theory related to the intersectional invisibility hypothesis (Purdie-Vaughns & Eibach, 2008), we hypothesized that stereotyping of minority men would be more strongly related to prejudice than stereotyping of minority women. Supporting our hypothesis, in both the United Kingdom (Study 1) and the United States (Study 2), when stereotyping of Black men and women were entered into the same regression model, only stereotyping of Black men predicted prejudice. Results were inconsistent in regard to South Asians and East Asians. Results are discussed in terms of the intersectional invisibility hypothesis (Purdie-Vaughns & Eibach, 2008) and the gendered nature of the relationship between stereotyping and attitudes.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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