Gaps in Transgender Medicine Content Identified Among Canadian Medical School Curricula
Bibliographic record
Abstract
Abstract Purpose: The transgender community is a diverse group that requires unique consideration in the healthcare setting. However, several studies have suggested that their needs are not currently being met by our medical system. Although the reason for this discrepancy is likely multifactorial, inadequate training of healthcare professionals to manage this population has been cited as a contributing factor. Methods: To evaluate the role that Canadian medical schools play in addressing these proposed deficits, program administrators were invited to provide curricular information detailing their delivery of transgender health, and medical students were surveyed to assess the impact of current curricula on their knowledge, attitudes, and experiences with regard to transgender health. Results: Six of fourteen schools provided curricular information about their instruction in transgender health and wide variation was found; 255/1152 University of British Columbia (UBC) students and 155/2358 students from eight other Canadian medical schools responded to the survey. Greater than 95% of responders agreed that transgender issues are important and should be addressed by physicians. However, fewer than 10% of students felt that they were sufficiently knowledgeable to do so. At UBC, there was no significant improvement in the self-reported knowledge levels after receiving the transgender-related curricula, and only 24% of students felt the topic was proficiently taught. Conclusion: This study showed that the majority of students who responded do not feel comfortable addressing the needs of transgender individuals in a healthcare setting and suggests that a reevaluation of related curricula may be warranted.
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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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".