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Record W2155279274 · doi:10.1177/2333393614560566

Interprofessional Collaboration

2015· article· en· W2155279274 on OpenAlex
Dawn Prentice, Joyce M. Engel, Karyn Taplay, Karl Stobbe

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueGlobal Qualitative Nursing Research · 2015
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsMcMaster UniversityRegional Municipality of NiagaraBrock University
FundersBrock University
KeywordsPerspective (graphical)Face (sociological concept)PsychologyMedical educationNatural (archaeology)NursingMedicineSociologyComputer science

Abstract

fetched live from OpenAlex

In this hermeneutic phenomenological study, we examined the experience of interprofessional collaboration from the perspective of nursing and medical students. Seventeen medical and nursing students from two different universities participated in the study. We used guiding questions in face-to-face, conversational interviews to explore students' experience and expectations of interprofessional collaboration within learning situations. Three themes emerged from the data: the great divide, learning means content, and breaking the ice. The findings suggest that the experience of interprofessional collaboration within learning events is influenced by the natural clustering of shared interests among students. Furthermore, the carry-forward of impressions about physician-nurse relationships prior to the educational programs and during clinical placements dominate the formation of new relationships and acquisition of new knowledge about roles, which might have implications for future practice.

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.

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)0.008
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.524
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.003

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 head0.344
GPT teacher head0.708
Teacher spread0.363 · 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