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Record W4250875701 · doi:10.4000/laboreal.4021

Encontros sobre o trabalho: reflexões sobre o uso desta ferramenta metodológica em pesquisas em Unidades de Tratamento Intensivo Neonatais

2015· article· pt· W4250875701 on OpenAlexaff
Letícia Pessoa Masson, Luciana Gomes, Jussara Brito

Bibliographic record

VenueLaboreal · 2015
Typearticle
Languagept
FieldHealth Professions
TopicHealth, Nursing, Elderly Care
Canadian institutionsOrthopaedic Innovation Centre
Fundersnot available
KeywordsWork (physics)SociologyPedagogyEngineering

Abstract

fetched live from OpenAlex

Buscamos discutir o uso de uma ferramenta metodológica, denominada “Encontros sobre o Trabalho”, que segue os princípios da Ergologia, visando propiciar o debate, a reflexão e o desenvolvimento da atividade de trabalho. A discussão é realizada a partir da apresentação de suas formas de uso em duas experiências de pesquisa que procuraram compreender-transformar a relação saúde-trabalho de profissionais de enfermagem em Unidades de Tratamento Intensivo Neonatais. Constatamos que esse dispositivo grupal apresenta um grande potencial para a transformação positiva no pensar-agir dos protagonistas do polo da atividade e do polo dos saberes formais, assim como nos meios do trabalho. Identificamos desafios e aprendizagens em sua operacionalização, referentes, especialmente, à linguagem e aos materiais utilizados para animar os Encontros, aos encaminhamentos efetivos e riscos de insucesso, ao seu caráter formativo e à sua importância para a conquista da 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)0.044
metaresearch head score (Gemma)0.055
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 score0.044
Threshold uncertainty score0.234

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0440.055
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0050.011
Scholarly communication0.0140.009
Open science0.0030.007
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0060.001

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 head0.109
GPT teacher head0.413
Teacher spread0.304 · 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

Citations5
Published2015
Admission routes1
Has abstractyes

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