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Da educação em serviço à educação continuada em um hospital federal

2020· article· pt· W3040154749 on OpenAlexaff
Camila Pureza Guimarães da Silva, Pacita Geovana Gama de Sousa Aperibense, Antônio José de Almeida Filho, Tânia Cristina Franco Santos, Sioban Nelson, María Angélica de Almeida Peres

Bibliographic record

VenueEscola Anna Nery · 2020
Typearticle
Languagept
FieldHealth Professions
TopicHealth, Nursing, Elderly Care
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsContinuing educationHumanitiesPhilosophyPolitical scienceMedicineMedical education

Abstract

fetched live from OpenAlex

RESUMO: Objetivo analisar as implicações da Educação em Serviço para o exercício do poder disciplinar dos enfermeiros na criação do serviço de Educação Continuada do Hospital Geral de Bonsucesso (HGB). Método Estudo histórico-social cujas fontes foram documentos escritos e depoimentos orais; utilizada a análise do discurso Foucaultiano. Resultados As atividades da Educação em Serviço no HGB passaram por dois períodos de descontinuidade e foram utilizadas como instrumento de poder disciplinar exercido pelas enfermeiras do hospital, capazes de controlar e organizar o serviço de enfermagem da instituição, fornecendo base para a criação do serviço de Educação Continuada. Conclusão e implicações para a prática a criação da Educação Continuada funcionou como um dispositivo utilizado pelas enfermeiras detentoras de saber e poder para execução do poder disciplinar, capaz de disciplinar e adestrar os funcionários, de forma sutil, evitando atitudes contrárias aos objetivos do serviço de enfermagem, na tentativa de garantir o controle e a qualificação do mesmo. Ao refletir sobre práticas educativas/ educação continuada estimula-se a transformação da assistência a partir das necessidades dos usuários do Sistema Único de Saúde (SUS), contribuindo, dessa forma, para a qualidade dos serviços de saúde.

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)0.020
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 score0.044
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0040.001
Scholarly communication0.0030.001
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.061
GPT teacher head0.373
Teacher spread0.312 · 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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Citations28
Published2020
Admission routes1
Has abstractyes

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