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Record W3135211073 · doi:10.1093/bjsw/bcab037

Social Work Faculty Engagement in Social Policy Practice: A Quantitative Study of the Canadian Experience

2021· article· en· W3135211073 on OpenAlexaffabout
Hugh Shewell, Karen Schwartz, Kim Ongaro

Bibliographic record

VenueThe British Journal of Social Work · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsCarleton University
Fundersnot available
KeywordsSocial policySocial workWork (physics)Social engagementPublic relationsSociologySocial changePolitical scienceSocial science

Abstract

fetched live from OpenAlex

Abstract This article reports on a quantitative study of how Canadian social work educators engage in social policy practice. The first part of the article contextualises social policy in Canada, explains how social policy has been incorporated into Canadian social work education and concludes by posing the research question. The second part presents the study’s findings of how and to what extent Canadian social work academics engage with social policy including its development, analysis and implementation. Thirty-one educators representing seventeen of Canada’s forty schools of social work responded to a standard questionnaire used in a collection of cross-national studies. The Canadian responses were analysed to determine (1) the level and type of engagement in policy including the perceived impact on social policy and (2) the institutional and individual factors associated with their engagement. Some comparisons are made with other countries studies. The third part of the article provides overall concluding comments linking the first part with the findings of the second, speculates on the reasons for some of the findings and poses some ideas for future research. Finally, it laments the increased focus of Canadian social work on individual pathology.

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)0.004
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.354
Threshold uncertainty score0.983

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.007
Science and technology studies0.0180.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.110
GPT teacher head0.456
Teacher spread0.346 · 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 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

Citations4
Published2021
Admission routes2
Has abstractyes

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