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Record W2162744235 · doi:10.1177/0969733012462048

Interprofessional collaboration-in-practice

2013· article· en· W2162744235 on OpenAlexaff
Carol Ewashen, Gloria McInnis-Perry, N J Murphy

Bibliographic record

VenueNursing Ethics · 2013
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsDalhousie UniversityUniversity of Prince Edward IslandUniversity of Calgary
Fundersnot available
KeywordsEngineering ethicsVirtue ethicsHealth careNursing ethicsSociologySituatedVirtueProfessional ethicsPoliticsInformation ethicsPolitical scienceLaw

Abstract

fetched live from OpenAlex

The main question examined is: How do nurses and other healthcare professionals ensure ethical interprofessional collaboration-in-practice as an everyday practice actuality? Ethical interprofessional collaboration becomes especially relevant and necessary when interprofessional practice decisions are contested. To illustrate, two healthcare scenarios are analyzed through three ethics lenses. Biomedical ethics, relational ethics, and virtue ethics provide different ways of knowing how to be ethical and to act ethically as healthcare professionals. Biomedical ethics focuses on situated, reflective, and nonabsolute principled justification, all things considered; relational ethics on intersubjective, professional, and institutional relations; and virtue ethics on prephilosophical tradition and what it means to be good and to be human embedded in social and political community. Analysis suggests that interprofessional collaboration-in-practice may be more rhetoric than actuality. Key challenges of interprofessional collaboration-in-practice and specific conditions perpetuating dissension and conflict are outlined with specific education and policy recommendations included.

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.731
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.003

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 head0.099
GPT teacher head0.563
Teacher spread0.464 · 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; both teacher heads agree on what is shown here.

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

Citations30
Published2013
Admission routes1
Has abstractyes

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