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Record W2468317512 · doi:10.1080/13561820.2016.1192589

A scoping review of interprofessional education within Canadian nursing literature

2016· review· en· W2468317512 on OpenAlexaffabout
Rachel Grant, Joanne Goldman, Karen LeGrow, Kathleen MacMillan, Mary van Soeren, Simon Kitto

Bibliographic record

VenueJournal of Interprofessional Care · 2016
Typereview
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsWestern UniversityToronto Metropolitan UniversityUniversity of TorontoDalhousie UniversityUniversity of Ottawa
Fundersnot available
KeywordsCINAHLInterprofessional educationPeer reviewNursingNurse educationGrey literatureMEDLINEHealth careNursing researchPsychologyMedical educationMedicinePolitical sciencePsychological intervention

Abstract

fetched live from OpenAlex

The purpose of this scoping review is to examine the nature of the interprofessional education (IPE) discussion that the Canadian nursing profession is having within the Canadian peer-reviewed nursing literature. An electronic database search of CINAHL was conducted using a modified Arksey & O'Malley scoping review framework. Peer-reviewed, English-language articles published in Canadian nursing journals from January 1981 to February 2016 were retrieved. Articles were included if they discussed IPE, or described an educational activity that met our conceptual definition of IPE. A total of 88 articles were screened, and 11 articles were eligible for analysis. Analysis revealed that this body of literature does not seem to be purposefully engaging Canadian nurses in a critical discourse about the role of IPE. The majority of articles located were reflective or commentaries. At the time of this review, there was a paucity of theoretically informed empirical research articles on IPE in the nursing literature. While IPE may be viewed by some critical scholars as a means of shifting the control of healthcare delivery traditionally held by medicine to other professions, our results suggest that this may not be the case in the Canadian nursing profession.

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)0.016
metaresearch head score (Gemma)0.056
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.679
Threshold uncertainty score0.638

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.056
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0380.053
Science and technology studies0.0040.002
Scholarly communication0.0060.003
Open science0.0030.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.039
GPT teacher head0.533
Teacher spread0.494 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations12
Published2016
Admission routes2
Has abstractyes

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