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Record W2296521366 · doi:10.1590/0034-7167.2016690125i

Metodologias qualitativas em pesquisa na saúde: referencial interpretativo de Patricia Benner

2016· article· pt· W2296521366 on OpenAlexaff
Raíssa Passos dos Santos, Eliane Tatsch Neves, Franco A. Carnevale

Bibliographic record

VenueRevista Brasileira de Enfermagem · 2016
Typearticle
Languagept
FieldHealth Professions
TopicHealth, Nursing, Elderly Care
Canadian institutionsMcGill UniversityMontreal Children's Hospital
Fundersnot available
KeywordsExistentialismThematic analysisPhenomenology (philosophy)HermeneuticsInterpretative phenomenological analysisPsychologyEpistemologyContext (archaeology)Phenomenological methodSociologyQualitative researchPhilosophySocial science

Abstract

fetched live from OpenAlex

RESUMO Objetivo: este artigo relata a experiência de utilização do referencial fenomenológico interpretativo de Patricia Benner em uma pesquisa de dissertação de mestrado. A fenomenologia interpretativa, pautada em referenciais filosóficos existenciais e de interpretação, possui como objetivo compreender as experiências humanas nos diversos mundos dos participantes da pesquisa. Os dados foram coletados por meio de entrevistas com nove enfermeiros, nos meses de novembro e dezembro de 2014. Resultados: o processo de análise dos dados, de acordo com o referencial de Benner, segue os passos: transcrição, codificação, análise temática e busca por casos paradigmáticos e exemplares. Para tanto, os conhecimentos prévios dos pesquisadores fazem parte da estrutura do projeto interpretativo, constituindo as vias de condução do estudo. Conclusão: o uso desse referencial teórico e metodológico constituiu-se em um desafio para a pesquisadora, porém demonstrou potencial ímpar para o desvelamento de fenômenos existenciais relacionados ao cotidiano dos participantes.

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)0.035
metaresearch head score (Gemma)0.058
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.035
Threshold uncertainty score0.186

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0350.058
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.006
Science and technology studies0.0070.016
Scholarly communication0.0160.007
Open science0.0020.008
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0070.001

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 head0.141
GPT teacher head0.450
Teacher spread0.309 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations20
Published2016
Admission routes1
Has abstractyes

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