Gender Inclusivity of Canadian Clinical Practice Guidelines Intended to Be Applied or Implemented Based on Sex or Gender: A Descriptive Study
Bibliographic record
Abstract
Purpose: The scope and implementation of clinical practice guidelines (CPGs) frequently depends on sex or gender considerations. Ideally, who is included in CPGs and how they are implemented would consider people of all sexes and genders, including trans and gender-diverse people, even if just to state there is little evidence. We evaluated levels of inclusion of trans and gender-diverse populations in relevant Canadian CPGs. Methods: We identified non-transition-related CPGs with sex- or gender-based scope or implementation considerations via environmental scan and expert consultation. CPG topics had to (1) traditionally apply to cisgender individuals; (2) include sex or gender in risk assessment; or (3) include sex- or gender-based recommendations. We searched the Canadian Medical Association InfoBase from 2015 to May 2023 for eligible CPGs. We assessed whether CPGs (1) mentioned trans or gender-diverse (TGD) individuals; (2) made recommendations for TGD care; (3) addressed implementation with TGD individuals; or (4) involved TGD individuals in CPG development. Results: Of 49 eligible CPGs, 22 were produced by government-sponsored organizations, 15 by professional societies, and 15 by disease-interest groups (3 jointly produced). Ten (20%) mentioned trans or gender-diverse people, 2 (4%) included relevant recommendations, 1 (2%) addressed implementation, and 1 (2%) included trans and gender-diverse individuals in development. Conclusion: Few Canadian CPGs with sex or gender implications recognized trans and gender-diverse people. CPG producers should support equitable care by including trans and gender-diverse individuals in sex- and gender-based CPGs by making recommendations or identifying that there was insufficient evidence.
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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 | 0.015 | 0.109 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.008 | 0.015 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".