Perceptions of women who confront hostile and benevolent sexism
Bibliographic record
Abstract
= 1315), we test a) whether confronting benevolent sexism is more costly for women than confronting hostile sexism and b) whether confronting some subtypes of benevolent sexism are more costly than others. We compared confrontations and non-confrontations of hostile sexism, benevolent sexism involving complementary gender differentiation (CGD), and benevolent sexism involving protective paternalism (PP). Surprisingly, confronting benevolent sexism was not more costly than confronting hostile sexism; a finding that replicated across studies and in two different contexts. Confronters of PP were evaluated more positively than confronters of CGD, but only when CGD embodied themes of gender essentialism (i.e., beliefs that men and women are naturally different). Confronters were mostly evaluated favorably relative to non-confronters and especially among women. Results imply that confronting benevolent sexism may have fewer consequences than anticipated.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".