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A percepção do enfermeiro sobre a contribuição das práticas de estágios extracurriculares para sua formação

2023· article· pt· W4390263941 on OpenAlexaff
Inez Silva de Almeida, Mayara da Silva Bazílio, Maria Regina Araújo Reicherte Pimentel, Juliana Fernandes, Fernanda Martins Cardoso, Carlana Santos Grimaldi Cabral de Andrade

Bibliographic record

VenueRevista Científica Multidisciplinar Núcleo do Conhecimento · 2023
Typearticle
Languagept
FieldHealth Professions
TopicHealth, Nursing, Elderly Care
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Objetivo: Analisar a percepção do enfermeiro sobre a contribuição das práticas de promoção da saúde em estágios extracurriculares, para a sua formação. Estudo qualitativo, descritivo, exploratório. O cenário foi um ambulatório de um hospital do estado do Rio de Janeiro. As participantes da pesquisa foram 9 enfermeiras. A técnica de coleta de dados ocorreu por meio de entrevista semi-estruturada, entre julho e agosto de 2021. Utilizou-se a análise de conteúdo de Bardin. A partir dos depoimentos emergiram duas categorias: Percepção do processo de promoção da saúde: mudanças na visão de mundo e Percepção do estágio para a bolsista: mudanças para a formação. Para as ex-bolsistas, os estágios extracurriculares desenvolvem na prática teorias que foram fomentadas em seu período de formação. As ações educativas dos projetos proporcionaram a aquisição de novos conhecimentos, a partir da interação com a clientela.

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)0.007
metaresearch head score (Gemma)0.019
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0030.001
Open science0.0010.002
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 head0.088
GPT teacher head0.458
Teacher spread0.369 · 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
Published2023
Admission routes1
Has abstractyes

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