Review of current 2SLGBTQIA+ inequities in the Canadian health care system
Bibliographic record
Abstract
Gender identity and sexual orientation are determinants of health that can contribute to health inequities. In the 2SLGBTQIA+ community, belonging to a sexual and/or gender minority group leads to a higher risk of negative health outcomes such as depression, anxiety, and cancer, as well as maladaptive behaviors leading to poorer health outcomes such as substance abuse and risky sexual behavior. Empirical evidence suggests that inequities in terms of accessibility to health care, quality of care, inclusivity, and satisfaction of care, are pervasive and entrenched in the health care system. A better understanding of the current Canadian health care context for individuals of the 2SLGBTQIA+ community is imperative to inform public policy and develop sensitive public health interventions to make meaningful headway in reducing inequity. Our search strategy was Canadian-centric and aimed at highlighting the current state of 2SLGBTQIA+ health inequities in Canada. Discrimination, patient care and access to care, education and training of health care professionals, and crucial changes at the systemic and infrastructure levels have been identified as main themes in the literature. Furthermore, we describe health care-related disparities in the 2SLGBTQIA+ community, and present available resources and guidelines that can guide healthcare providers in narrowing the gap in inequities. Herein, the lack of training for both clinical and non-clinical staff has been identified as the most critical issue influencing health care systems. Researchers, educators, and practitioners should invest in health care professional training and future research should evaluate the effectiveness of interventions on staff attitudinal changes toward the 2SLGBTQIA+ community and the impact on patient outcomes.
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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 | 0.008 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.025 | 0.054 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".