Not all prejudices are experienced equally: Comparing experiences of racism and sexism in female minorities
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
Research exploring the perspectives of stigmatized people has examined general processes related to experiencing prejudice. Past work, however, has invoked the assumption that prejudices against different group memberships are experienced in a similar manner. Across three studies we directly compare experiences of racism and sexism among female minorities and show, in contrast, that people respond to different forms of prejudice in distinct ways. In Study 1 we examined the attributions invoked by Asian women to explain prejudice and discovered that participants made stronger internal attributions to explain racism than sexism. In Study 2 we investigated emotional reactions to prejudice and found that Asian women report experiencing more depression following a race-based rejection than a gender-based rejection. In Study 3 we observed that Asian women reported perceiving more racism than sexism in their environments. Implications for advancing theories of prejudice experiences are discussed.
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 | 0.000 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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