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Record W7034576172

Understanding Perceptions of Non-Indigenous Medical Educators’ Professional Competency for the Integration and Delivery of Indigenous Health Curriculum in Medicine

2024· dissertation· en· W7034576172 on OpenAlexfundaboutno aff

Bibliographic record

VenueMacSphere (McMaster University) · 2024
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicFern and Epiphyte Biology
Canadian institutionsnot available
FundersCanadian Medical Association
KeywordsIndigenousCurriculumConceptualizationCultural safetyCultural competenceTraditional knowledgeCompetence (human resources)Action (physics)Cultural diversity
DOInot available

Abstract

fetched live from OpenAlex

The Canadian medical education system is to increase curricula on Indigenous health as outlined in the Truth and Reconciliation Commission’s (TRC) Call to Action #24; medical schools need instructors with cultural competency. As most instructors are non-Indigenous Medical Educators (NIMEs), medical educators urgently need to understand what it means to be culturally competent within Indigenous health and engage with the TRC Calls to Action #24, which states: “We call upon medical and nursing schools in Canada to require all students to take a course dealing with Aboriginal health issues... This will require skills-based training in intercultural competency, conflict resolution, human rights, and anti-racism (TRC, 2015, 3).” This research examines what constitutes competency in teaching Indigenous health curricula in medical education. Using critical race theory for analysis, three areas are explored: 1. understanding competency; 2. the role of Indigenous health in medicine; and 3. educator and learner perspectives. One-to-one interviews were conducted with Indigenous learners and medical educators, frontline non-Indigenous medical educators and senior leadership from across Canada’s medical schools. The data allowed for a robust understanding of what competency to teach Indigenous health means when the participants in systems of Indigenous health curricula share their views on NIMEs and account for how Indigenous and Western knowledge often difer in conceptualization and expression. The analysis provided recommendations for NIME training and a snapshot of NIME professional competencies from their perspectives and those of people receiving their teaching. From this research, an initial framework of ethical standards for the teaching of Indigenous health was developed. This framework can be instrumental in developing territorial-based standards between medical schools and local Indigenous communities in which medical schools are situated. It can also support medicine’s regulatory, policy, and academic bodies of medicine in addressing the TRC Call to Action #24.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.910
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.035
GPT teacher head0.272
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes2
Has abstractyes

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