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Record W4303431064 · doi:10.7202/1091516ar

RETHINKING REGULATION: INCLUSIONS, EXCLUSIONS AND STRUGGLES

2022· article· en· W4303431064 on OpenAlexvenueno aff
Donna Baines, Natalie Clark, Jeane Riley

Bibliographic record

VenueCanadian social work review · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsnot available
Fundersnot available
KeywordsLicensureGovernment (linguistics)RacismPublic administrationPolitical scienceIndigenousInclusion (mineral)SociologyHealth carePolicy analysisPower (physics)HarmCriminologyLawPublic relationsGender studies

Abstract

fetched live from OpenAlex

A recent government report in British Columbia on anti-Indigenous racism in health care calls into question the claim that regulating health care professionals protects the public and ensures a high standard of professional, ethical care. Licensure and regulation have long been debated in social work with strong advocates on each side. The first section of this article revisits the historical and contemporary pro-registration and pro-inclusion arguments. Drawing on publicly available documents central to licensure and regulation in BC, the article then draws on two policy analysis frameworks, namely Indigenous Intersectional-Based Policy Analysis and Bacchi’s framework to explore “what is the problem represented to be” and who is positioned as problematic and erased or delegitimized within these processes. The analysis shows that the regulation debate is a series of practices of power that frame which issues will be “raised and which will not be discussed” such as “harm” and “protection”, while simultaneously eclipsing Indigenous and other non-dominant cultural perspectives and concerns. Our analysis further suggests that mandatory registration constructs the problems facing social workers in depoliticized and narrow ways that do not extend social justice, reconciliation, or decolonization, and require a serious rethink at this moment of change and challenge.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.903
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0200.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0240.000

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 head0.057
GPT teacher head0.352
Teacher spread0.295 · 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

Citations4
Published2022
Admission routes1
Has abstractyes

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