Toward an inclusive digital health system for sexual and gender minorities in Canada
Bibliographic record
Abstract
Most digital health systems (DHS) are unable to capture gender, sex, and sexual orientation (GSSO) data beyond a single binary attribute with female and male options. This binary system discourages access to preventative screening and gender-affirming care for sexual and gender minority (SGM) people. We conducted this 1-year multi-method project and cocreated an action plan to modernize GSSO information practices in Canadian DHS. The proposed actions are to: (1) Envisage an equity- and SGM-oriented health system; (2) Engage communities and organizations to modernize GSSO information practices in DHS; (3) Establish an inclusive GSSO terminology; (4) Enable DHS to collect, use, exchange, and reuse standardized GSSO data; (5) Integrate GSSO data collection and use within organizations; (6) Educate staff to provide culturally competent care and inform patients on the need for GSSO data; and (7) Establish a central hub to coordinate efforts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".