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Record W4283021762 · doi:10.1177/10497315221109486

Clinical Social Work Practice in Canada: A Critical Examination of Regulation

2022· article· en· W4283021762 on OpenAlexaboutno aff
Toula Kourgiantakis, Rachelle Ashcroft, Faisa Mohamud, Alison Benedict, Eunjung Lee, Shelley L. Craig, Karen M. Sewell, Marjorie C. Johnston, Alan McLuckie, Deepy Sur

Bibliographic record

VenueResearch on Social Work Practice · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsnot available
Fundersnot available
KeywordsSocial workClinical PracticeEquity (law)Best practiceDiversity (politics)Political scienceMedicineMedical educationPublic relationsNursingLaw

Abstract

fetched live from OpenAlex

Purpose: The most common form of social work (SW) practice in Canada is clinical which requires specialized knowledge and advanced clinical skills. The SW profession is more than 100 years old, but regulation is new to Canada and presently most jurisdictions have regulatory bodies to advance safe, competent, and ethical practices. Regulatory bodies establish admission requirements, standards of practice, ethical guidelines, supervision, continuing education requirements, and measures for complaints and discipline. Methods: This article examines regulation of SW practice in Canada with a focus on registration requirements, clinical SW designation, use of controlled acts such as psychotherapy and diagnosis, supervision, continuing education, technology, private practice, and how regulatory bodies address diversity, equity, reconciliation, racism, and discrimination. Results: This critical examination of clinical SW practice found inconsistent standards across the country. Conclusions: It is important to harmonize the three pillars including education, association, and regulation to strengthen clinical SW practice in Canada.

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)0.086
metaresearch head score (Gemma)0.175
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: none
Teacher disagreement score0.582
Threshold uncertainty score0.676

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0860.175
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0130.016
Science and technology studies0.0350.039
Scholarly communication0.0200.004
Open science0.0060.007
Research integrity0.0030.008
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 head0.271
GPT teacher head0.571
Teacher spread0.300 · 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

Citations20
Published2022
Admission routes1
Has abstractyes

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