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Record W4387143884 · doi:10.47634/cjcp.v56i3.72700

Mental Health Professionals' Views on the Regulation of Psychotherapy in Ontario

2023· article· en· W4387143884 on OpenAlexaffvenueabout
Leslie Marie Vesely, Nicola Gazzola, John Beaton, Olga Smoliak

Bibliographic record

VenueCanadian Journal of Counselling and Psychotherapy · 2023
Typearticle
Languageen
FieldPsychology
TopicCounseling Practices and Supervision
Canadian institutionsUniversity of GuelphUniversity of OttawaInstitute for Work & Health
Fundersnot available
KeywordsStatutory lawMental healthAmbiguityScope (computer science)PsychotherapistPsychologyGovernment (linguistics)Scope of practicePublic relationsPolitical scienceHealth careLaw

Abstract

fetched live from OpenAlex

In Canada, statutory regulation for the mental health professions is a provincial or territorial matter. In 2007, the Ontario government introduced the Psychotherapy Act (PA), which details the scope of practice as well as the authorized act of psychotherapy. The PA established the College of Registered Psychotherapists of Ontario (CRPO) to regulate its members in the service of protecting the public. Given the long history of contestation and ambiguity surrounding the definition of psychotherapy, the PA represents an important historic moment for practitioners in Ontario. However, little research has been conducted on psychotherapy practitioners’ experiences and perspectives on professional regulation. This study qualitatively explored perspectives on, and experiences with, the PA among regulated mental health practitioners who have access to the act of psychotherapy in Ontario, including psychotherapists, nurses, physicians, occupational therapists, psychologists, and social workers. The study provides insights into the ways that these professional groups are impacted by the regulation of psychotherapy and has implications for the future implementation of statutory regulation.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.757
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.072
GPT teacher head0.362
Teacher spread0.290 · 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

Citations2
Published2023
Admission routes3
Has abstractyes

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