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Record W6996282226

Review of âBehind the Rhetoric: Mental Health Recovery in Ontarioâ (Jennifer Poole)

2015· article· en· W6996282226 on OpenAlexaffabout

Bibliographic record

VenueThe Journal of Macrodynamic Analysis (Memorial University of Newfoundland) · 2015
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsNorthwestern Polytechnic
Fundersnot available
KeywordsMental healthPsychological interventionMEDLINEHealth carePublic healthDisease
DOInot available

Abstract

fetched live from OpenAlex

Through discussing how the recovery model has become popular within the mental health system in Ontario, Poole offers an outstanding critique of recovery’s rhetoric. Using Foucault’s concepts of “discursive formation”, Poole demonstrates that the recovery model borrows concepts from biomedical discourse, and therefore is not as new and empowering as people believe. She illustrates how the recovery model actually provides a very narrow definition of how one must “recover” from “mental illness” that serves to silence psychiatric survivors that may be critical of the recovery movement. Poole also illustrates how the recovery movement is influenced by neo-liberalism, as it has become a growing industry funded by the pharmaceutical industry. Further, she offers readers insight into the inherent ‘whiteness’ of the recovery movement, which emphasizes personal responsibility, and subscribes to western ideas of individualism and western definitions of what mental health is.

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)0.010
metaresearch head score (Gemma)0.037
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.465
Threshold uncertainty score0.936

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.037
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.007
Science and technology studies0.0050.006
Scholarly communication0.0050.003
Open science0.0020.003
Research integrity0.0080.008
Insufficient payload (model declined to judge)0.0090.002

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 head0.084
GPT teacher head0.350
Teacher spread0.266 · 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 designNot applicable
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

Citations0
Published2015
Admission routes2
Has abstractno

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