A community-based study to set the policy agenda for the well-being of 2GSBTQ+ men in Ontario, Canada
Bibliographic record
Abstract
Abstract Two-Spirit, Gay, Bisexual, Transgender, and Queer (2SGBTQ+) men face significant health inequity. This article reports on two phases of a study conducted in conjunction with the Gay Men’s Sexual Health Alliance (GMSH) to examine 2SGBTQ+ men’s health inequity. First, an environmental scan of existing Ontario government health policy was conducted to identify specific gaps. Second, six focus groups of GMSH Alliance members (n = 21) were conducted to understand the impact of policy gaps and identify potential strategies to address them from the community’s perspective. We argue that to meet the wellness needs of the community, community development and healthy public policies are appropriate strategies. The environmental scan confirmed that there is currently very limited policy content specific to 2SGBTQ+ men’s wellness and mental health. Data from focus groups were consistent with the scan. GMSH Alliance members struggled to serve their community in the absence of sufficient resources. Participants also expressed an interest in advocacy, but they felt that they lacked the skills to do so. It is clear that 2SGBTQ+ men face population-specific health risks, and much work is needed to advocate for 2SGBTQ+-centred well-being policy. Future work should develop a policy that focuses on addressing many of the issues raised in this research, while also contributing to the achievement of health equity for 2SGBTQ+ men.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.017 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".