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Record W4408068505 · doi:10.1007/978-3-031-70106-1_6

Foregrounding the Relational Dimensions of Interprofessional Collaboration: A Communication Perspective

2025· book-chapter· en· W4408068505 on OpenAlexaff
Kirstie McAllum, Stéphanie Fox, Laura Ginoux, L. D. Meyer

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsForegroundingPerspective (graphical)SociologyPsychologyComputer scienceLinguisticsPhilosophyArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract Interprofessional collaboration requires the development and maintenance of multiple relationships: with other healthcare providers, supervisors, as well as patients and their families who need to be considered as team members. This chapter documents two distinct orientations to the relationships essential for collaboration: a task orientation and a relationship orientation. A task orientation concentrates on how collegial relationships enable collaborative work to get done more efficiently and effectively, whereas a relationship orientation focuses on how members of interprofessional teams build and consolidate positive interpersonal relationships in the context of their collaboration. The chapter analyzes how role (mis)understanding and lack of trust generate relational challenges in the context of interprofessional collaboration before turning to communicative practices that underpin the creation of compassionate teams, organizations, and workplaces.

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)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.009
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.010
Scholarly communication0.0090.006
Open science0.0010.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0060.001

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 head0.043
GPT teacher head0.432
Teacher spread0.389 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations1
Published2025
Admission routes1
Has abstractyes

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