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Challenging contemporary mental health policy: time to assuage the coercion?

2002· review· en· W2131150199 on OpenAlexaff
Ben Hannigan, John R. Cutcliffe

Bibliographic record

VenueJournal of Advanced Nursing · 2002
Typereview
Languageen
FieldPsychology
TopicHealthcare Decision-Making and Restraints
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMental healthCoercion (linguistics)Government (linguistics)Context (archaeology)LegislatureHealth policyHealth careMental health lawPublic relationsPolitical scienceMedicinePsychiatryLaw

Abstract

fetched live from OpenAlex

BACKGROUND: In the United Kingdom (UK) and elsewhere throughout the world, the policy and legal frameworks that surround the provision of mental health care are becoming increasingly coercive. For example, emerging mental health policy in the UK includes a commitment to the introduction of compulsory treatment in the community. AIMS: In this paper, our aims are: to explore the context in which this more coercive mental health policy has arisen in the UK; to challenge the assumptions and the evidence that lie behind the introduction of proposed new mental health policies; and to consider the impact that a more coercive policy is likely to have on the practice of mental health nursing. DISCUSSION: In the UK, representatives of central government have declared that 'care in the community has failed'. This view has been reinforced by media representations of mental health issues. Policy documents have drawn attention to the risks posed by people with mental illnesses. Correspondingly, proposed initiatives emphasize the need to more closely 'manage' people with mental health problems, and set out a new legislative and policy framework to achieve this. We question the assumptions and evidence that underlie these planned new developments. We argue that, contrary to government assertions, there is no unequivocal evidence that 'community care' has failed. We observe, too, that people with mental health difficulties are often amongst the most vulnerable members of society. Finally, we consider the impact that a more coercive policy framework will have on the work of mental health nurses, and argue that the shift towards a more 'controlling' role is likely to run counter to what many nurses see as the 'core' of their work.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.977
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.001

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 head0.109
GPT teacher head0.497
Teacher spread0.388 · 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 designOther design
Domainnot available
GenreReview

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

Citations42
Published2002
Admission routes1
Has abstractyes

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