Anti-feminist backlash: The role of system justification in the rejection of feminism
Bibliographic record
Abstract
System justification theory (SJT) posits that people are motivated to believe that the social system they live in is fair, desirable, and how it should be, especially in contexts that heighten the system justification motive. Past researchers have suggested that opposition to feminists may be motivated by the threat that feminism presents to the legitimacy of the status quo, but this hypothesis has not been tested empirically. In this article, we present three studies that directly test the idea that antifeminist backlash can be motivated by system justification. Studies 1 and 2 experimentally manipulated the SJ motive and a female target’s feminist identification (feminist vs. nonfeminist). Study 3 tested the hypothesis by measuring participants’ SJ motivation via an individual difference measure. Participants disagreed more with identical statements about gender issues made by the feminist target than the nonfeminist target, but only when the system justification motive was heightened (Study 2) or chronically high (Study 3).
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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 | 0.011 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.010 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| 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".