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Pesquisa participativa sob a lógica do cuidado: análise compartilhada em um CAPS AD

2022· article· pt· W4312676383 on OpenAlexaboutno aff
Octávia Cristina Barros, Octávio Domont de Serpa

Bibliographic record

VenueRevista Latinoamericana de Psicopatologia Fundamental · 2022
Typearticle
Languagept
FieldHealth Professions
TopicHealth, Nursing, Elderly Care
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPsychologyPhilosophy

Abstract

fetched live from OpenAlex

A pesquisa procurou explorar as experiências de adoecimento com base no ponto de vista dos usuários de um CAPS AD III. A metodologia empregada neste estudo se baseia em um desenho qualitativo e se divide em duas etapas. Na primeira, foi realizada uma entrevista semiestruturada com os participantes — Entrevista Narrativa de Adoecimento McGill-MINI —, e, na segunda, os participantes foram parte integrante do processo de validação, análise dos resultados e elaboração do arcabouço temário. Os resultados anunciam narrativas atravessadas por desamparo psíquico, abandono familiar, perdas e falta de credibilidade, efeito de um processo excludente em que a droga se sobrepõe ao sujeito. A pesquisa participativa sob a lógica do cuidado (Tangvald-Pedersen & Bongaardt, 2016) possibilitou um diálogo reflexivo acerca da experiência de adoecimento aproximando pesquisadores e participantes, que são como diferentes contadores de histórias, permitindo que a tessitura do fenômeno descrito pudesse enriquecer a compreensão uns dos outros.

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)0.016
metaresearch head score (Gemma)0.052
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 score0.017
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.052
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.008
Science and technology studies0.0060.007
Scholarly communication0.0100.009
Open science0.0020.012
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0140.002

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 head0.067
GPT teacher head0.390
Teacher spread0.322 · 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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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