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Record W2108886154 · doi:10.1191/0969733004ne692oa

Exploring The Heart Ofethical Nursing Practice: implications for ethics education

2004· article· en· W2108886154 on OpenAlexafffund
Gweneth Hartrick Doane, Bernie Pauly, Helen Brown, Gladys McPherson

Bibliographic record

VenueNursing Ethics · 2004
Typearticle
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsUniversity of British ColumbiaUniversity of Victoria
FundersAssociated Medical Services
KeywordsNursingNursing ethicsMedicinePsychologyEngineering ethics

Abstract

fetched live from OpenAlex

The limitations of rational models of ethical decision making and the importance of nurses' human involvement as moral agents is increasingly being emphasized in the nursing literature. However, little is known about how nurses involve themselves in ethical decision making and action or about educational processes that support such practice. A recent study that examined the meaning and enactment of ethical nursing practice for three groups of nurses (nurses in direct care positions, student nurses, and nurses in advanced practice positions) highlighted that humanly involved ethical nursing practice is also simultaneously a personal process and a socially mediated one. Of particular significance was the way in which differing role expectations and contexts shaped the nurses' ethical practice. The study findings pointed to types of educative experiences that may help nurses to develop the knowledge and ability to live in and navigate their way through the complex, ambiguous and shifting terrain of ethical nursing 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)0.052
metaresearch head score (Gemma)0.066
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.052
Threshold uncertainty score0.274

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0520.066
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0110.066
Scholarly communication0.0230.027
Open science0.0040.015
Research integrity0.0130.016
Insufficient payload (model declined to judge)0.0100.001

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 head0.653
GPT teacher head0.662
Teacher spread0.008 · 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

Citations67
Published2004
Admission routes2
Has abstractyes

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