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Record W1995881233 · doi:10.1080/13561820701653227

Theory and practice in interprofessional ethics: A framework for understanding ethical issues in health care teams

2007· article· en· W1995881233 on OpenAlexaff
Phillip G. Clark, Cheryl Cott, Theresa J. K. Drinka

Bibliographic record

VenueJournal of Interprofessional Care · 2007
Typearticle
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsTeamworkEngineering ethicsOrganizational ethicsHealth careSet (abstract data type)BioethicsField (mathematics)Interprofessional educationFunction (biology)Foundation (evidence)SociologyPsychologyNursingMedicineComputer sciencePolitical scienceEngineering

Abstract

fetched live from OpenAlex

Interprofessional teamwork is an essential and expanding form of health care practice. While moral issues arising in teamwork relative to the patient have been explored, the analysis of ethical issues regarding the function of the team itself is limited. This paper develops a conceptual framework for organizing and analyzing the different types of ethical issues in interprofessional teamwork. This framework is a matrix that maps the elements of principles, structures, and processes against individual, team, and organizational levels. A case study is presented that illustrates different dimensions of these topics, based on the application of this framework. Finally, a set of conclusions and recommendations is presented to summarize the integration of theory and practice in interprofessional ethics, including: (i) importance of a framework, (ii) interprofessional ethics discourse, and (iii) interprofessional ethics as an emerging field. The goal of this paper is to begin a dialogue and discussion on the ethical issues confronting interprofessional teams and to lay the foundation for an expanding discourse on interprofessional ethics.

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)0.073
metaresearch head score (Gemma)0.196
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
Consensus categoriesMetaresearch, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.794
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0730.196
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0030.041
Insufficient payload (model declined to judge)0.0000.000

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 head0.111
GPT teacher head0.594
Teacher spread0.482 · 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

Citations76
Published2007
Admission routes1
Has abstractyes

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