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Record W2774488767 · doi:10.1111/ijsw.12302

Rethinking Values and Ethics in Social Work edited by RichardHugman and JanCarter. 2016: London, UK, Palgrave Macmillan, 230 pp. ISBN 978‐1‐137‐45502‐4

2017· article· en· W2774488767 on OpenAlexaboutno aff
Donna McAuliffe

Bibliographic record

VenueInternational Journal of Social Welfare · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsnot available
Fundersnot available
KeywordsCitationSociologySocial workLibrary scienceMedia studiesLawPolitical scienceComputer science

Abstract

fetched live from OpenAlex

Richard Hugman and Jan Carter have published a book that is timely and relevant to, as they say, social work in turbulent times. With 15 chapters from contributors in Australia, Canada, the USA, UK, South Africa and Hong Kong, they have successfully created a text that moves discussions of values and ethics in social work to a new level and depth. The opening preface of the book is chilling in its description of a ‘small, steamy, tropical island in the Pacific, denuded of its natural resources first by colonisation and then by commercial rent seekers, and now hoping to earn its way by hosting refugee detention camps for wealthy Western nations’ (p. vii). The case unfolds to show how social workers are placed in an unenviable position of having to uphold professional values, while being employed by organisations that perpetuate human rights violations. This theme is continued throughout the book in a number of chapters, where the connections between human rights, social justice and social work ethics are debated and delineated. Many cases are used to illustrate the complexities of assessing need, intervening on the basis of a multitude of factors and reflecting on alternate possibilities.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.803
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.038
GPT teacher head0.374
Teacher spread0.336 · 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 teacher head, not a consensus.

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
Published2017
Admission routes1
Has abstractyes

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