Building a Movement: Mobilizing more men for violence prevention, gender equality, and social justice in Canada: Recommendations for the Government of Canada
Bibliographic record
Abstract
The Government of Canada is committed to ending violence and advancing gender equality. To strengthen these efforts, a national strategy is urgently needed that will support the engagement and mobilization of more men and boys to stop violence before it starts and achieve gender and social justice. This report responds to Women and Gender Equality Canada’s interest in advancing this work and provides concrete and evidence-informed opportunities and recommendations to support the research, collaborations, partnerships, network-building, capacity building, processes, and funding needed to do just that. It was undertaken as part of the Calling In Men research project and builds on previous recommendations made to the Government of Canada and Women and Gender Equality Canada.
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.
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 | 0.019 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.037 | 0.017 |
| Scholarly communication | 0.021 | 0.009 |
| Open science | 0.009 | 0.018 |
| Research integrity | 0.009 | 0.012 |
| Insufficient payload (model declined to judge) | 0.026 | 0.003 |
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".