Power, Ethnic Origin, and Sexual Objectification
Bibliographic record
Abstract
In this study, we investigated the effects of primed power on sexual objectification of Caucasian and Asian men and women. As in previous studies, sexual objectification was assessed using an inversion paradigm with face–body compound stimuli. Previous work has shown that participants primed to power do not show the typical drop in recognition performance for inverted face–body compound stimuli, suggesting that they process these stimuli in terms of their individual features, in a manner akin to objects, and quite different from the way in which faces and bodies are normally processed (i.e., configurally). Caucasian male and female participants were primed to high or neutral-power before engaging in an old/new recognition task involving sexualized face–body compound images of Caucasian and Asian men and women. Participants primed to high-power showed a decreased inversion effect for Caucasian models of the opposite gender, but not for Asian models. Thus, power exerts different effects on this specific type of social perception, depending on the ethnic origin of the target. We discuss our results in the context of the extant literature on power and with reference to media stereotyping of Caucasians and Asians.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.005 | 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".