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Record W2071339723 · doi:10.1080/13561820500082974

Factors in implementing interprofessional education and collaborative practice initiatives: Findings from key informant interviews

2005· article· en· W2071339723 on OpenAlexaffabout
Keegan K. Barker, Carmela Bosco, Ivy Oandasan

Bibliographic record

VenueJournal of Interprofessional Care · 2005
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsUniversity of TorontoToronto Western HospitalUniversity Health Network
Fundersnot available
KeywordsInterprofessional educationTerminologyConstructivist grounded theoryGovernment (linguistics)Medical educationGrounded theoryHealth careNursingQualitative researchPsychologyMedicineSociologyPolitical science

Abstract

fetched live from OpenAlex

Health Canada (the federal government department in Canada responsible for health issues) commissioned a research team to conduct an environmental scan and research report in order to understand interprofessional education and collaborative patient-centred practice (IECPCP). This paper presents the findings from semi-structured telephone interviews with key informants conducted as part of the environmental scan. Grounded theory analysis was employed in order to identify factors associated with interprofessional education and collaborative practice initiatives. These factors were grouped according the following themes: lack of consensus regarding terminology; the need for both champions and external support; sensitization to the effects of professional culture, and logistics of implementation. Findings are discussed related to the literature and to the other papers included in this supplement to the Journal of Interprofessional Care.

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)0.036
metaresearch head score (Gemma)0.088
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 score0.036
Threshold uncertainty score0.190

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0360.088
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0070.005
Scholarly communication0.0050.006
Open science0.0020.005
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0010.000

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 head0.031
GPT teacher head0.467
Teacher spread0.435 · 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

Citations124
Published2005
Admission routes2
Has abstractyes

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