Beyond Allyship: Motivations for Advantaged Group Members to Engage in Action for Disadvantaged Groups
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
White Americans who participate in the Black Lives Matter movement, men who attended the Women's March, and people from the Global North who work to reduce poverty in the Global South-advantaged group members (sometimes referred to as allies) often engage in action for disadvantaged groups. Tensions can arise, however, over the inclusion of advantaged group members in these movements, which we argue can partly be explained by their motivations to participate. We propose that advantaged group members can be motivated to participate in these movements (a) to improve the status of the disadvantaged group, (b) on the condition that the status of their own group is maintained, (c) to meet their own personal needs, and (d) because this behavior aligns with their moral beliefs. We identify potential antecedents and behavioral outcomes associated with these motivations before describing the theoretical contribution our article makes to the psychological literature.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it