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Record W3039778988 · doi:10.22456/2238-152x.104150

O Comitê Cidadão e o trajeto participativo da pesquisa GAM

2020· article· pt· W3039778988 on OpenAlexaff
Thais Mikie de Carvalho Otanari, Maria Lourdes Rodriguez del Barrio

Bibliographic record

VenueRevista Polis e Psique · 2020
Typearticle
Languagept
FieldHealth Professions
TopicHealth, Nursing, Elderly Care
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

O artigo aborda duas questões centrais no desenvolvimento contemporâneo da pesquisa em Saúde Mental: a inclusão dos saberes comunitários, ou da experiência, e a participação direta das pessoas na construção dos conhecimentos. Para isso, analisa a experiência de participação cidadã no projeto que traduziu e adaptou um instrumento que prevê um lugar central aos usuários na tomada de decisões do tratamento farmacológico em psiquiatria, o guia GAM (Gestão Autônoma da Medicação). Mais especificamente, procura-se compreender se a metodologia participativa permite transformar as relações de saber-poder e quais são suas implicações. Nossa conclusão é que, através de uma metodologia científica que inclui e valoriza os sujeitos em suas diferenças, a participação pôde tensionar posições hierárquicas pré-estabelecidas, favorecendo um contexto em que os cidadãos, mais empoderados e autônomos, ampliam a capacidade de atuação nas práticas da rede de pesquisa, contribuindo para a desconstrução de condições sócio-históricas de exclusão.

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)0.008
metaresearch head score (Gemma)0.009
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0110.007
Scholarly communication0.0120.006
Open science0.0020.015
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0150.001

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 head0.184
GPT teacher head0.443
Teacher spread0.259 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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