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Record W4226248617 · doi:10.1177/10497323211069681

Challenging the Constraints of Neoliberalism and Biomedicalism: Repositioning Social Work in Mental Health

2022· article· en· W4226248617 on OpenAlexaffabout
Catrina Brown, Marjorie Johnstone, Nancy Ross, Kaitrin Doll

Bibliographic record

VenueQualitative Health Research · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsUniversity of TorontoDalhousie University
Fundersnot available
KeywordsNeoliberalism (international relations)Mental healthAutonomySocial workRationalization (economics)Social WelfareSociologyWelfare statePublic relationsSocial policyPolitical scienceMedicineEconomic growthSocial scienceEconomicsPsychiatryPolitics

Abstract

fetched live from OpenAlex

This article explores the impact of neoliberalism and biomedicalism on social work mental health care practice through presenting the results of a Canadian provincial study which illustrates the experiences of social work service users, providers, and supervisors. While Canada has a universal health care program, the intensification of the free-market approach is evident in the shifts from public sector support to growing rationalization and marked cutbacks to the provision of social welfare services. The specific impact of neoliberal economic restraint on social justice in mental health services has pressured practitioners to adopt medicalized, short-term strategies, under efficiency-based models. The participants in this study reported significant co-occurring concerns with the state of mental health service delivery, and results suggest social work is increasingly co-opted by the conservative individualizing, pathologizing, and contextualizing dominant biomedical framework in the provision of mental health social services and lack of professional practice autonomy.

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)0.045
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.963
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0450.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0120.002
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.423
GPT teacher head0.625
Teacher spread0.202 · 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

Citations25
Published2022
Admission routes2
Has abstractyes

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