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Record W1965027000 · doi:10.1177/096973300000700507

Ethical Issues in Public Health Nursing

2000· article· en· W1965027000 on OpenAlexafffundabout
Kathleen Oberle, Sandra Christine Tenove

Bibliographic record

VenueNursing Ethics · 2000
Typearticle
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsUniversity of Calgary
FundersCanadian Nurses Foundation
KeywordsNursingPublic healthContext (archaeology)Ethical issuesPublic health nursingQualitative researchPsychologyHealth careMedicineSociologyEngineering ethicsPolitical science

Abstract

fetched live from OpenAlex

This qualitative study was designed to explore ethical issues in public health nursing in the Canadian context, and to begin to identify strategies to support ethical practice. Twenty-two public health nurses, 11 in rural and 11 in urban settings, were asked to describe ethical problems they had experienced in the course of their work. These participants most often described situations that required a relational response rather than an active choice between options. Their goal was to optimize the good, while at the same time maintaining a supportive relationship. Analysis revealed five interrelated themes, each with several subthemes: relationships with health care professionals; systems issues; character of relationships; respect for persons; and putting self at risk. It was clear that all aspects of public health nursing have ethical components.

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)0.031
metaresearch head score (Gemma)0.045
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.186
Threshold uncertainty score0.370

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0310.045
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0320.044
Scholarly communication0.0100.005
Open science0.0020.007
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.451
GPT teacher head0.637
Teacher spread0.186 · 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 designNot applicable
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

Citations47
Published2000
Admission routes3
Has abstractyes

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