Approaches to Indigenous health within interprofessional education: a scoping review protocol
Bibliographic record
Abstract
OBJECTIVE: This scoping review will explore the depth, breadth, and nature of existing literature on educational approaches to Indigenous health within interprofessional education learning activities, and provide a summary of available literature, identify gaps in the research, and recommend areas for further exploration. INTRODUCTION: Interprofessional education learning activities comprise sessions where health care learners work collaboratively to address and improve the health outcomes of a given population, such as health needs among Indigenous communities. A preliminary search for existing reviews was conducted across several databases. Published literature on Indigenous health within interprofessional education learning activities exists; however, there is no comprehensive review on this topic. INCLUSION CRITERIA: This review will consider literature on existing educational approaches to Indigenous health within interprofessional education learning activities, in particular the approaches used to teach cultural awareness, sensitivity, competency, safety, and/or humility. It will consider all forms of English-language evidence, including quantitative studies, qualitative studies, mixed-method studies, and gray literature. Participants include health care and social care professionals, educators, and students within interprofessional education learning activities. METHODS: The JBI scoping review methodology will be used to guide our research. The following databases will be searched: MEDLINE, CINAHL Plus, PsycINFO, ProQuest ASSIA, Indigenous Studies Portal, and ERIC. We will also hand search reference lists and explore gray literature. Two reviewers will screen the search results and extract included studies using data extraction forms. The data will be presented in summary tables and a narrative summary.
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 | 0.124 | 0.089 |
| Meta-epidemiology (narrow) | 0.004 | 0.006 |
| Meta-epidemiology (broad) | 0.011 | 0.011 |
| Bibliometrics | 0.027 | 0.022 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.007 | 0.010 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.066 | 0.019 |
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".