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Record W1582668298

Interprofessional Collaboration and Culturally-safe Aboriginal Health Care

2009· article· fr· W1582668298 on OpenAlexaffabout
Ellen Rukholm, Lorraine Carter, Denise Newton-Mathur

Bibliographic record

Venuenot available
Typearticle
Languagefr
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsLaurentian University
Fundersnot available
KeywordsInterprofessional educationCultural safetyTeamworkHealth careMedical educationCulturally appropriateNursingVariety (cybernetics)MedicineFamily medicinePolitical science
DOInot available

Abstract

fetched live from OpenAlex

As part of a Health Canada’s commitment to Interprofessional Education for Collaborative Patient-Centred Practice, this project called Interprofessional Collaboration: Culturally-informed Aboriginal Health Care project enhances cultural awareness of a specific Aboriginal community and interprofessional teamwork in health care. A unique asynchronous web-based learning and research initiative, the project brought the teachings and beliefs of Elders from what is known as the North Shore, an area north of Lake Huron between Sudbury and Sault Ste. Marie, Ontario, Canada to undergraduate health education students in a variety of disciplines. This paper describes the educational development process of the resulting online module as well as findings and changes made based on the pilot offering of Interprofessional Collaboration: Culturally-informed Aboriginal Health Care by Laurentian University in Sudbury, ON. Since the pilot, the module has been translated into French.

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 imitation

Not 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.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.006
Scholarly communication0.0050.003
Open science0.0010.015
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.012
GPT teacher head0.453
Teacher spread0.441 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations2
Published2009
Admission routes2
Has abstractyes

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Same topicInterprofessional Education and CollaborationFrench-language works237,207