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Record W1984687891 · doi:10.1080/10508420802623682

Believers and Skeptics: Where Social Worker Situate Themselves Regarding the Code of Ethics

2009· article· en· W1984687891 on OpenAlexaffabout
Marshall Fine, Eli Teram

Bibliographic record

VenueEthics & Behavior · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsSkepticismEthical codeVariety (cybernetics)Engineering ethicsEXPOSECode (set theory)Code of conductSociologyFaithMeta-ethicsSocial psychologyEnvironmental ethicsPsychologyLawNursing ethicsEpistemologyPolitical sciencePhilosophySet (abstract data type)EngineeringComputer science

Abstract

fetched live from OpenAlex

Based on individual and focus-group interviews, this article describes how social workers in a variety of settings and geographical areas within Ontario approached ethical issues in their daily practices. Two primary approaches to professional ethics emerge from the data: principle based and virtue based, reflecting the orientation of groups we label believers and skeptics, respectively. The code of ethics appears to be the fulcrum from which our participants swing. The believers show faith in the code of ethics and the skeptics are dubious that codes are necessarily in the best interests of clients. The article describes the thinking behind the actions of the believers and skeptics and explores possibilities for future practice and research with respect to decision-making regarding ethical issues in the social work profession.

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)0.020
metaresearch head score (Gemma)0.046
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.108

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.046
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0170.027
Scholarly communication0.0100.007
Open science0.0020.009
Research integrity0.0040.007
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 head0.127
GPT teacher head0.446
Teacher spread0.320 · 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

Citations22
Published2009
Admission routes2
Has abstractyes

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