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Record W7023802962

Practicing the Public Good Exploring Ethical Issues in Public Health Practice

2012· dissertation· en· W7023802962 on OpenAlexaboutno aff

Bibliographic record

VenueKnowledge Commons (Lakehead University) · 2012
Typedissertation
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsnot available
Fundersnot available
KeywordsNucleofectionArticular cartilage damageGestational periodHyporeflexiaDiafiltrationPretext
DOInot available

Abstract

fetched live from OpenAlex

Everyday ethics refers to the issues and decision-making practitioners are routinely faced with in their daily work. A quantitative, descriptive study examined everyday ethical issues in public health practice. The theoretical framework was based on Jameton's (1984) concepts of moral uncertainty, moral dilemma and moral distress in nursing. Moral distress may have negative consequences that ultimately lead to job dissatisfaction and leaving the profession. This phenomenon has been studied extensively in clinical practice, but comparatively little in public health practice. A questionnaire was administered to employees at the Thunder Bay District Health Unit (TBDHU) in Thunder Bay, Ontario, Canada. This instrument included an extensively-modified moral
\ndistress scale (MDS) (Corley, Elswick, Gorman & Clor, 2001) supplemented by questions about demographics, ethics capacity and personal reflection. Altogether, moral problems were reported at low mean frequencies and intensities. Generally, front line providers and managers and supervisors experienced moral problems at higher levels than the sample average. Furthermore, education, membership in a professional association and job experience had a statistically-significant impact on moral problems. Finally, themes of recent moral or ethical dilemmas included: relationships; different interests/perspectives; fairness; knowledge sharing; and personal issues.

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)0.027
metaresearch head score (Gemma)0.072
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.922
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0270.072
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0060.000
Scholarly communication0.0000.003
Open science0.0020.001
Research integrity0.0030.046
Insufficient payload (model declined to judge)0.0010.002

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 head0.297
GPT teacher head0.477
Teacher spread0.179 · 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 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

Citations0
Published2012
Admission routes1
Has abstractyes

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