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Record W2158468275 · doi:10.1177/0969733007073694

Ethical Sensitivity: State of Knowledge and Needs for Further Research

2007· review· en· W2158468275 on OpenAlexaff
Kathryn Weaver

Bibliographic record

VenueNursing Ethics · 2007
Typereview
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsEngineering ethicsMeaning (existential)Qualitative researchPsychologyEthical leadershipSociologyEpistemologySocial psychologySocial sciencePsychotherapist

Abstract

fetched live from OpenAlex

Ethical sensitivity was introduced to caring science to describe the first component of decision making in professional practice; that is, recognizing and interpreting the ethical dimension of a care situation. It has since been conceptualized in various ways by scholars of professional disciplines. While all have agreed that ethical sensitivity is vital to practice, there has been no consensus regarding its definition, its characteristics, the conditions needed for it to occur, or the outcomes to professionals and society. The purpose of this article is to explore the meaning of the concept of ethical sensitivity based on a review of the professional literature of selected disciplines. Qualitative content analysis of the many descriptors found within the literature was conducted to enhance understanding of the concept and identify its essential characteristics. Ethical sensitivity is considered to be an emerging concept with potential utility in research and 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)0.061
metaresearch head score (Gemma)0.085
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: Review · Consensus signal: Review
Teacher disagreement score0.061
Threshold uncertainty score0.324

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0610.085
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0060.010
Science and technology studies0.0030.008
Scholarly communication0.0140.023
Open science0.0050.006
Research integrity0.0130.009
Insufficient payload (model declined to judge)0.0130.002

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 head0.749
GPT teacher head0.723
Teacher spread0.026 · 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
GenreReview

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

Citations104
Published2007
Admission routes1
Has abstractyes

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