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Record W1503607323

Autonomia e cogestão na prática em saúde mental: o dispositivo da gestão autônoma da medicação (GAM)

2013· article· pt· W1503607323 on OpenAlexaboutno aff
Eduardo Passos, Analice de Lima Palombini, Rosana Teresa Onocko Campos, Sandro Rodrigues, Jorge Melo, Paula Milward Maggi, Cecília de Castro e Marques, Lívia Zanchet, Michele da Rocha Cervo, Bruno Ferrari Emerich

Bibliographic record

VenueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2013
Typearticle
Languagept
FieldHealth Professions
TopicHealth, Nursing, Elderly Care
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceMental healthPsychologyPhilosophyPsychiatry
DOInot available

Abstract

fetched live from OpenAlex

O artigo aborda a articulacao entre autonomia e cogestao nas praticas em saude mental no Brasil, baseado em estudo multicentrico. Tal estudo objetivou a elaboracao do Guia Brasileiro da Gestao Autonoma da Medicacao (Guia GAM-BR), com base na traducao e adaptacao do Guia GAM desenvolvido no Quebec – instrumento dirigido a pessoas com transtornos mentais graves. Uma primeira versao do Guia GAM traduzida e adaptada ao contexto brasileiro foi utilizada em Grupos de Intervencao (GI) com usuarios de servicos de saude mental nos campos da pesquisa. A construcao da versao final do Guia GAM brasileiro incluiu as modificacoes propostas pelos GI em cada campo, debatidas em reunioes multicentricas com a participacao de pesquisadores, trabalhadores e usuarios integrantes dos GI. No curso da pesquisa, a estrategia GAM assumiu o desafio de propor-se como pratica cogestiva, compatibilizando exercicio da autonomia, direito e protagonismo dos usuarios com o funcionamento e cultura organizacional das instituicoes de saude mental.

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)0.004
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.084
Threshold uncertainty score0.167

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.006
Scholarly communication0.0030.002
Open science0.0010.004
Research integrity0.0010.001
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 head0.040
GPT teacher head0.316
Teacher spread0.276 · 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 designObservational
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

Citations15
Published2013
Admission routes1
Has abstractyes

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