Engaging White Men in Allyship for Structural Change: A Systematic Review
Bibliographic record
Abstract
While most violent crime declined during COVID-19, domestic and gender-based violence either remained the same or increased in most jurisdictions. Some social movements have turned to engaging men in change for gender equity initiatives—confronting intersecting oppressions. In this systematic review, we examine peer-reviewed studies on White men’s allyship across five electronic databases which resulted in seven studies that met the inclusion criteria. White men’s allyship is an emerging research area that is primarily qualitative and exploratory with few high-quality studies. Antecedents of White men’s allyship were a sense of fairness, justice, and equality; compassion; personal experiences of oppression; and caring community membership along with leadership skills. The processes allies experienced as they developed were turning points, learning and knowledge acquisition, joining social movements and engaging in social action, and skill building and maturation. Learning from the critiques of allyship is an opportunity for White men to engage in relationally accountable allyship.
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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 | 0.009 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".