Under-served and overlooked: The need for LGBTQ2SIA+ military family research in Canada
Bibliographic record
Abstract
Research shows that a bidirectional relationship exists between the health and well-being of military members and their families. Military family research identified many gaps in the current knowledge base, including minimal existing research and a lack of diversity in the families represented, including LGBTQIA2S+ families, who have unique experiences and needs. The Canadian military has a fraught history with its LGBTQIA2S+ members, including homophobic and transphobic policies and practices, the most well-known being the Purge, which was the sanctioned investigation, harassment, and removal of LGBTQIA2S+ members (and those suspected to be LGBTQIA2S+). This history created a unique context in which these members live and work. Despite this, there is a dearth of research specifically geared toward learning more about the experiences of LGBTQIA2S+ members and their families. This article situates the need for dedicated LGBTQIA2S+ military family research in Canada to advocate for expanded programs, services, and policies to move forward the Canadian Armed Forces' (CAF) defence policy, Strong, Secure, Engaged, to ensure all members of the CAF and their families feel heard and supported.
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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 | 0.024 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.034 | 0.009 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".