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Record W2055045400 · doi:10.1080/13561820500067132

Interprofessional learning and higher education structural barriers

2005· article· en· W2055045400 on OpenAlexaff
John Gilbert

Bibliographic record

VenueJournal of Interprofessional Care · 2005
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsInterprofessional educationScope (computer science)Scope of practiceHuman servicesService (business)Health careMedical educationNursingPublic relationsMedicineSociologyEngineering ethicsPolitical scienceBusinessEngineering

Abstract

fetched live from OpenAlex

Structural changes need to be made within universities such that interprofessional education for patient-centred collaborative practice becomes a responsibility that crosses faculty jurisdictions and is accepted as the responsibility of all associated health and human service programs. In communities, the patient or client is the centre of professional attention requiring care that goes beyond the skill and scope of any one profession. Notions about collaboration inform and drive interprofessional education and should lead to sustainable system changes within centres of advanced education that ensure a permanent place for interprofessional education in all health and human service programs. This chapter explores the many barriers to achieving this goal, and offers insights into their removal from one university's experience.

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)0.020
metaresearch head score (Gemma)0.059
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.059
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0120.010
Scholarly communication0.0120.007
Open science0.0020.024
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0210.001

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 head0.433
Teacher spread0.421 · 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

Citations273
Published2005
Admission routes1
Has abstractyes

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