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Record W1493506041 · doi:10.1300/j010v35n01_11

Mental Health System Reform

2002· article· en· W1493506041 on OpenAlexaffabout
Wes Shera, Uri Aviram, Bill Healy, Shulamit Ramon

Bibliographic record

VenueSocial Work in Health Care · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicHealthcare innovation and challenges
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMental healthMarketizationMandateService delivery frameworkLegislatureSocial workHealth policyWork (physics)Public relationsBusinessEconomic growthPolitical sciencePublic administrationHealth careService (business)EconomicsMedicineMarketingChina

Abstract

fetched live from OpenAlex

In recent years many countries have embarked on various types of health and mental health reform. These reforms have in large part been driven by governments' concerns for cost containment which has, in turn, been driven by an increasing process of global marketization and the need to control national deficits. A critical issue in these reforms is the increased emphasis on the use of "market mechanisms" in the delivery of health and mental health services. This paper uses a policy analysis framework to compare recent developments in the mental health sector in Canada, the United States, Britain and Australia. The common framework to be used for this will focus on: the defining characteristics of the society; legislative mandate; sectorial location (within or separate from health sector); funding streams; organising values of the system; locus of service delivery; service technologies; the role of social work; interprofessional dynamics; the role of consumers; and evaluation of outcomes at multiple levels. This analysis provides an opportunity to explore similarities and differences in mental system reform and in particular identify the challenges for social work in the field of mental health in the 21st century.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.980
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.075
GPT teacher head0.392
Teacher spread0.317 · 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

Citations13
Published2002
Admission routes2
Has abstractyes

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