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Record W2017129708 · doi:10.3109/13561820.2012.751900

Making space: Integrating meaningful interprofessional experiences into an existing curriculum

2012· article· en· W2017129708 on OpenAlexaff
Diane MacKenzie, Brenda Merritt

Bibliographic record

VenueJournal of Interprofessional Care · 2012
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsDalhousie University
Fundersnot available
KeywordsCurriculumInterprofessional educationAccreditationMedical educationProcess (computing)Curriculum developmentSpace (punctuation)Engineering ethicsMedicinePsychologyPedagogyHealth careEngineeringComputer sciencePolitical science

Abstract

fetched live from OpenAlex

Many health professional education programs have instituted, or are in the process of developing, structures for implementing interprofessional education (IPE). Professional organizations are also adopting IP competencies for their respective memberships and accreditations. Our IPE design and educational framework was informed by evidence gathered from professional organizations; the students' lived experience with traditional approaches and evolving IPE designs and data from our school's longitudinal curriculum evaluation study. This paper briefly describes the evolution and design of an embedded IPE program within an existing master's level curriculum - which meets not only curriculum competencies but also nationally recognizes IPE competencies. In addition, the embedded program articulates with a mandatory faculty-wide IPE initiative. The creation of embedded IPE within existing courses allowed for enriched learning opportunities for both discipline-specific and IPE knowledge without changing the overall curriculum structure.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.375
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.060
GPT teacher head0.500
Teacher spread0.440 · 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.

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

Citations13
Published2012
Admission routes1
Has abstractyes

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