Supportive contact and LGBT collective action: The moderating role of membership in specific groups.
Bibliographic record
Abstract
A growing body of literature suggests that positive cross-group contact between members of advantaged and disadvantaged groups can undermine disadvantaged group members’ collective action engagement. It has also been proposed that supportive contact (i.e., positive contact with advantaged group members who express explicit support for social change) may be a special form of contact that might increase, rather than reduce collective action engagement among disadvantaged group members. In the present research, we tested this proposition by asking Gay (N = 96) and Lesbian (N = 100) Australians to recall a previous positive interaction with a heterosexual friend who was either very supportive or somewhat supportive of Lesbian, Gay, Bisexual, and Transgendered (LGBT) rights (i.e., equal marriage, adoption, and surrogacy rights). Results revealed that the effect of supportive contact on collective action intentions depended on the participants’ specific disadvantaged group membership. For Gay men, those who recalled supportive contact reported greater collective action intentions. The opposite pattern emerged for Lesbian women. These findings suggest that supportive contact has the power to enhance or undermine collective action intentions among the disadvantaged. Which of these occurs appears to depend on the specific disadvantaged group to which one belongs. The psychological underpinnings of these effects, the theoretical implications, and future research directions are discussed.
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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 | 0.003 | 0.014 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".