Development of an online educational toolkit for sexual orientation and gender identity minority nursing care
Bibliographic record
Abstract
OBJECTIVE: to develop and implement an online education resources to address a gap in nursing education regarding the concept of cultural humility and its application to healthcare encounters with persons who identify as lesbian, gay, bisexual, transgender, queer, intersex (LGBTQI) or Two-Spirit. Improved understanding of LGBTQI and Two-Spirit community health issues is essential to reducing the healthcare access barriers they currently face. METHOD: an online educational toolkit was developed that included virtual simulation games and curated resources. The development process included community involvement, a team-building meeting, development of learning outcomes, decision-point maps and scriptwriting for filming. A website and learning management system was designed to present learning objectives, curated resources, and the virtual games. RESULTS: the Sexual Orientation and Gender Identity Nursing Toolkit was created to advance cultural humility in nursing practice. The learning toolkit focuses on encounters using cultural humility to meet the unique needs of LGBTQI and Two-Spirit communities. CONCLUSION: our innovative online educational toolkit can be used to provide professional development of nurses and other healthcare practitioners to care for LGBTQI and Two-Spirit individuals.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.005 |
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".