Pilot Feasibility Study: Nurses' Preparedness to Care for Racialized Gender-Diverse People
Bibliographic record
Abstract
The nursing profession perpetuates an outdated model that fails to address the health concerns of racialized gender-diverse people. Evidence supports that this population experiences poorer health outcomes, care-avoiding habits, and incompetent healthcare providers. A literature review illuminated gaps in the nursing lens when considering gender-diverse identities outside of Whiteness. An intersectionality framework and cultural humility were used to explore the contexts in which nurses provide care. To fill this knowledge gap, the proposed research question was: How prepared are nurses to provide care to racialized gender-diverse people? A questionnaire was developed by modifying three pre-existing instruments. The online questionnaire served as a pilot feasibility study to collect preliminary baseline descriptive cross-sectional data about Ontario nurses' training, education, knowledge, attitudes, and beliefs about racialized gender-diverse people. Findings indicated potential gaps in training and education that may affect racialized gender-diverse peoples' healthcare. Recommendations are provided for future research and interventions.
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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 | 0.011 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".