Gender-affirming care in undergraduate nursing education: a scoping review protocol
Bibliographic record
Abstract
INTRODUCTION: Transgender and gender-diverse (TGD) people face a multitude of barriers to safe, accessible healthcare. One way to overcome access inequities is through the provision of gender-affirming care. Gender-affirming care is culturally safe and engaged care that values TGD identities and is focused on depathologising TGD people. Additionally, gender-affirming care encompasses awareness and support of TGD individuals as unique beings, including supporting gender-affirming medical goals for those who are interested. The discipline of nursing is well situated to advocate for gender-affirming care, however, receives little undergraduate education in the subject. Undergraduate schools of nursing (including faculty and curriculum) are in a crucial position to implement gender-affirming care, though how they have done this is not widely known. Our scoping review aims to understand how Canadian and US undergraduate schools of nursing teach and integrate gender-affirming education. METHODS AND ANALYSIS: , reported on as per the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews. The review will be completed in 2023, with the database searches carried out in spring 2023, followed by screening and analysis. ETHICS AND DISSEMINATION: Ethics approval is not required for this protocol. To aid in knowledge translation, a visual representation of the findings will be created. Results from the final scoping review will be published in a peer-reviewed journal, promoted on social media to schools of nursing, and presented at conferences and seminars. PROTOCOL REGISTRATION NUMBER: Open Science Framework (https://doi.org/10.17605/OSF.IO/Q68BD).
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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 | 0.126 | 0.096 |
| Meta-epidemiology (narrow) | 0.005 | 0.006 |
| Meta-epidemiology (broad) | 0.012 | 0.010 |
| Bibliometrics | 0.019 | 0.016 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.010 | 0.009 |
| Insufficient payload (model declined to judge) | 0.079 | 0.020 |
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".