Bibliographic record
Abstract
For the first time, the broad health issues, needs and concerns of LGBT+ people in Canada were taken up by the federal government’s Standing Committee on Health in 2019. The findings of their consultations with LGBT+ Canadians produced a report that at once captures the breadth of input received, and provides an opportunity for accountable state response to LGBT+ health needs in the form of research, education, policy, funding and programming, yet questions arise as to the socio-political approach that will ultimately be taken. This focus on the health of LGBT+ Canadians follows decades of grassroots and sometimes state-funded research on this very issue. This study undertook a critical content analysis, premised on the queer liberation theory of The Health of LGBTQIA2 Communities in Canada report issued by the Standing Committee on Health. Although the report, for the most part, covers a breadth of broad LGBT+ health issues (a noted shift from the predominance of HIV/AIDS), the depth to which the Standing Committee took up and absorbed such issues is far less apparent. The heavy emphasis on entry-level recommendations by which to take up important LGBT+ health issues undermines a more progressive, liberationist approach that would more effectively address these concerns.
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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.032 | 0.010 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".