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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 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)0.048
metaresearch head score (Gemma)0.023
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.145
Threshold uncertainty score0.414

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0480.023
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.003
Science and technology studies0.0280.239
Scholarly communication0.0200.012
Open science0.0030.026
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0030.000

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 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

Citations25
Published2022
Admission routes2
Has abstractyes

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