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AS HISTÓRIAS DE VIDA COMO TRAMAS DE FIOS NA COMPOSIÇÃO DA PROFESSORALIDADE

2016· article· pt· W4229999753 on OpenAlexaff
Jussara Midlej, Marcos Villela Pereira

Bibliographic record

VenueRevista Brasileira de Pesquisa (Auto)Biográfica · 2016
Typearticle
Languagept
FieldSocial Sciences
TopicEducation Pedagogy and Practices
Canadian institutionsSexuality Education Resource Centre
Fundersnot available
KeywordsHumanitiesArtPhilosophy

Abstract

fetched live from OpenAlex

Este texto trata de uma investigação-formação realizada numa abordagem (auto)biográfica, entre 2013 e 2014, numa turma de Pedagogia, integrada ao Plano Nacional de Formação de Professores da Educação Básica (PARFOR), em colaboração com a Universidade Estadual do Sudoeste da Bahia (UESB), no campus de Jequié. As escritas de si, concretizadas nos memoriais, e as ações realizadas nos ateliês deram-se num plano extensional de recolha de informações, em diferentes circunstâncias e contextos, com a finalidade de expandir o campo dos possíveis, com retornos aos materiais produzidos no processo profissional e formativo. As conversações, como ações de reciprocidade, foram relacionadas à triangulação formativa e às histórias de vida, em contextos de pesquisa e formação. Os agrupamentos, com repetidas análises compreensivas das informações produzidas, demonstraram alargar as perspectivas docentes e ampliar as características formativas dos atos de narrar-se e às práticas educacionais cotidianas. Nos partícipes, o acréscimo das percepções de si e o aguçamento de seus entendimentos acerca das situações e das experiências ficaram patentes; contribuíram para a concepção da formação como autoformação, demonstrando que o ser humano, ao viver experiências de si rearranja, atualiza-se, diferencia-se continuamente, produz forças vitais criadoras de estados inéditos de ser professor.

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)0.007
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.695
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0030.002
Scholarly communication0.0020.001
Open science0.0020.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0120.003

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 head0.084
GPT teacher head0.402
Teacher spread0.318 · 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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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