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Record W6964359253 · doi:10.25384/sage.c.6818308

Knowledge Gaps Regarding Indigenous Health in Occupational Therapy: A National Survey

2023· other· en· W6964359253 on OpenAlexaboutno aff

Bibliographic record

VenueSage Journals Data · 2023
Typeother
Languageen
FieldEnvironmental Science
TopicEcology and biodiversity studies
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousThematic analysisOccupational therapyOccupational safety and healthCommissionWork (physics)Action (physics)

Abstract

fetched live from OpenAlex

<b>Background.</b> There is a need for the occupational therapy profession to respond to the Truth and Reconciliation Commission of Canada Calls to Action and work towards supporting the health and well-being of Indigenous Peoples. <b>Purpose.</b> (1) To determine the knowledge gaps of occupational therapists about Indigenous health and (2) to create recommendations to address identified gaps and inform responses from the profession. <b>Method.</b> A national needs survey was created and distributed to occupational therapists across Canada to determine the knowledge of occupational therapists about Indigenous health. Survey results were analyzed using thematic analysis and descriptive statistics. <b>Findings.</b> Data collected from 364 survey responses informed six distinct themes representing knowledge gaps of occupational therapists related to Indigenous health as follows: lack of foundational knowledge, power relations, lifelong learner, need for appropriate tools/approaches, respectful collaboration, and environmental influences. <b>Implications.</b> The project offers insight into the role of the occupational therapy profession in the process of reconciliation. Insights are focused on decolonizing occupational therapy practice, building trusting relationships with Indigenous Peoples, and the provision of appropriate training for occupational therapists to engage in culturally safer practices.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.348
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0110.002

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 head0.194
GPT teacher head0.380
Teacher spread0.186 · 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; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreOther

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
Published2023
Admission routes1
Has abstractyes

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