Interactive Effects of Obvious and Ambiguous Social Categories on Perceptions of Leadership: When Double-Minority Status May Be Beneficial
Bibliographic record
Abstract
Easily perceived identities (e.g., race) may interact with perceptually ambiguous identities (e.g., sexual orientation) in meaningful but elusive ways. Here, we investigated how intersecting identities impact impressions of leadership. People perceived gay Black men as better leaders than members of either single-minority group (i.e., gay or Black). Yet, different traits supported judgments of the leadership abilities of Black and White targets; for instance, warmth positively predicted leadership judgments for Black men but dominance positively predicted leadership judgments for White men. These differences partly occurred because of different perceptions of masculinity across the intersection of race and sexual orientation. Indeed, both categorical (race and sex) and noncategorical (trait) social information contributed to leadership judgments. These findings highlight differences in the traits associated with leadership in Black and White men, as well as the importance of considering how intersecting cues associated with obvious and ambiguous groups moderate perceptions.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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; both teacher heads agree on what is shown here.
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".