Transforming Masculinities Through Cross-Cultural Collaboration: Reflections on Building a Community of Practice Framework
Bibliographic record
Abstract
Interdisciplinary, local, regional, and cross-regional efforts are required to further men’s gender justice engagement on a global scale. There is limited understanding of how cross-regional collaborations account for intersectionality, geo-political differences among stakeholders, and the value of local strategies when designing and sharing prevention frameworks. Catalyzed by emerging and long-standing gender equity movements, our interdisciplinary research team from Canada, the Caribbean, Nepal, and Pakistan employed a community of practice (CoP) framework to share and mobilize research and experiential knowledge with the purpose of promoting regional and cross-regional strategies to involve men in gender justice efforts. Through a collective process, we co-created position statements, process dimensions, and key CoP activities to root our international collaboration. In this article, we emphasize the unique local contexts for our work and the learnings that emerged from our CoP. We propose a framework that can be used to advance collective and interdisciplinary agendas across global contexts and further the work of groups committed to transformative social change.
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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 | 0.103 | 0.054 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.046 | 0.113 |
| Scholarly communication | 0.028 | 0.024 |
| Open science | 0.007 | 0.040 |
| Research integrity | 0.011 | 0.014 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".