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INTRODUZINDO A INVESTIGAÇÃO NARRATIVA NOS CONTEXTOS DE NOSSAS VIDAS: UMA CONVERSA SOBRE NOSSO TRABALHO COMO INVESTIGADORES NARRATIVOS

2016· article· pt· W4250294718 on OpenAlexaff
Dilma Mello, Shaun Murphy, Jean Clandinin

Bibliographic record

VenueRevista Brasileira de Pesquisa (Auto)Biográfica · 2016
Typearticle
Languagept
FieldHealth Professions
TopicDigital Storytelling and Education
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsArtHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

O texto relata nossas experiências como investigadores narrativos para destacar aspectos da investigação narrativa que, frequentemente, criam dificuldades para novos pesquisadores a esta forma relacional de pesquisa. A investigação narrativa é o estudo da experiência entendida narrativamente. Dessa forma, chamamos a atenção para a investigação narrativa como um fenômeno sob estudo e metodologia para o estudo. Isso por si só, frequentemente, cria confusão para aqueles que são novos na investigação narrativa. Destacamos três tensões particulares que, frequentemente, causam dificuldades para os pesquisadores. Engajando no início da narrativa autobiográfica, mudando de textos de campo para textos de pesquisa e conduzindo investigações narrativas tornadas propositais para justificativas pessoais, teóricas/práticas e sociais foram as três tensões que selecionamos. Baseando em investigações narrativas contínuas e recentemente concluídas, Dilma, Shaun e Jean tornaram explícitas as maneiras como mudaram de textos de campo provisórios para textos finais de pesquisa.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.184
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.002
Science and technology studies0.0030.003
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.005

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 head0.058
GPT teacher head0.343
Teacher spread0.285 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations4
Published2016
Admission routes1
Has abstractyes

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