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Record W2166843264 · doi:10.1080/13561820500081745

Interprofessional teamwork: Professional cultures as barriers

2005· article· en· W2166843264 on OpenAlexaff
Pippa Hall

Bibliographic record

VenueJournal of Interprofessional Care · 2005
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsTeamworkJargonSocializationHealth professionsProfessional developmentInterprofessional educationMedical educationHealth carePsychologyNursingMedicinePedagogySociologyPolitical scienceSocial psychology

Abstract

fetched live from OpenAlex

Each health care profession has a different culture which includes values, beliefs, attitudes, customs and behaviours. Professional cultures evolved as the different professions developed, reflecting historic factors, as well as social class and gender issues. Educational experiences and the socialization process that occur during the training of each health professional reinforce the common values, problem-solving approaches and language/jargon of each profession. Increasing specialization has lead to even further immersion of the learners into the knowledge and culture of their own professional group. These professional cultures contribute to the challenges of effective interprofessional teamwork. Insight into the educational, systemic and personal factors which contribute to the culture of the professions can help guide the development of innovative educational methodologies to improve interprofessional collaborative 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.

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)0.032
metaresearch head score (Gemma)0.086
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.170

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0320.086
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0140.010
Scholarly communication0.0100.009
Open science0.0030.019
Research integrity0.0030.005
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 head0.012
GPT teacher head0.446
Teacher spread0.434 · 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

Citations1,390
Published2005
Admission routes1
Has abstractyes

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