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Record W2603040601

Interprofessional education in academic family medicine teaching units

2009· article· en· W2603040601 on OpenAlexvenueaboutno aff
David Price, Michelle Howard, Linda Hilts, Lisa Dolovich, Lisa McCarthy, Allyn Walsh, Lynn Dykeman

Bibliographic record

VenueCanadian Family Physician · 2009
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsnot available
Fundersnot available
KeywordsInterprofessional educationTeamworkMedical educationMedicineHealth careVariety (cybernetics)Health professionalsNursingCollaborative CarePrimary careFamily medicineComputer science
DOInot available

Abstract

fetched live from OpenAlex

PROBLEM ADDRESSED The new family health teams (FHTs) in Ontario were designed to enable interprofessional collaborative practice in primary care; however, many health professionals have not been trained in an interprofessional environment. OBJECTIVE OF PROGRAM To provide health professional learners with an interprofessional practice experience in primary care that models teamwork and collaborative practice skills. PROGRAM DESCRIPTION The 2 academic teaching units of the FHT at McMaster University in Hamilton, Ont, employ 6 types of health professionals and provide learning environments for family medicine residents and students in a variety of health care professions. Learners engage in formal interprofessional education activities and mixed professional and learner clinical consultations. They are immersed in an established interprofessional practice environment, where all team members are valued and contribute collaboratively to patient care and clinic administration. Other contributors to the success of the program include the physical layout of the clinics, the electronic medical record communications system, and support from leadership for the additional clinical time commitment of delivering interprofessional education. CONCLUSION This academic FHT has developed a program of interprofessional education based partly on planned activities and logistic enablers, and largely on immersing learners in a culture of long-standing interprofessional collaboration.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.481
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.051
GPT teacher head0.434
Teacher spread0.383 · 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.

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

Citations11
Published2009
Admission routes2
Has abstractyes

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