Flattering to deceive: Why people misunderstand benevolent sexism.
Bibliographic record
Abstract
Perceptions of warmth play a central role in social cognition. Seven studies use observational, correlational, and experimental methods to examine its role in concealing the functions of benevolent sexism (BS). Together, Studies 1 (n = 297), 2 (n = 252), and 3 (n = 219) indicated that although women recall experiencing benevolent (vs. hostile) sexism more often, they protest it less often, because they see it as warm. In Studies 4 (n = 296) and 5 (n = 361), describing men as high in BS caused them (via warmth) to be seen as lower in hostile sexism (HS) and more supportive of gender equality. In Study 6 (n = 283) these findings were replicated and extended, revealing misunderstanding of relationships between BS and a wide array of its correlates. In Study 7 (n = 211), men experimentally described as harboring warm (vs. cold) attitudes toward women were perceived as higher in BS but lower in known correlates of BS. These findings demonstrate that the warm affective tone of BS, particularly when displayed by men, masks its ideological functions. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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How this classification was reachedexpand
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 | 0.001 | 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) | 0.001 | 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 teacher head, 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".