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Record W4396861832 · doi:10.1177/10608265241254240

Engaging White Men in Allyship for Structural Change: A Systematic Review

2024· review· en· W4396861832 on OpenAlex
Jeff Halvorsen, Tamara Humphrey, Liza Lorenzetti, Mario Rolle

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Journal of Men s Studies · 2024
Typereview
Languageen
FieldSocial Sciences
TopicTourism, Volunteerism, and Development
Canadian institutionsSt. Mary's UniversitySaint Mary's UniversityUniversity of VictoriaUniversity of Calgary
Fundersnot available
KeywordsWhite (mutation)Systematic reviewPsychologyPolitical scienceMEDLINEBiology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.247
Threshold uncertainty score0.686

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.165
GPT teacher head0.438
Teacher spread0.273 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it