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Narrar a vulnerabilidade escolar: concepção de uma abordagem metodológica

2020· article· pt· W3109976918 on OpenAlexaff
Marie‐Claude Bernard, Alice Vanlint, Hélène Makdissi

Bibliographic record

VenueRevista Brasileira de Pesquisa (Auto)Biográfica · 2020
Typearticle
Languagept
FieldPsychology
TopicPsychology and Mental Health
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsHumanitiesSociologyPsychologyPhilosophy

Abstract

fetched live from OpenAlex

Neste artigo, propomos uma abordagem metodológica para o estudo da vulnerabilidade relacionada às dificuldades escolares da criança na perspectiva de três atores: a criança, os pais e o professor.Adotando uma abordagem compreensiva de inspiração etnográfica e clínica, elaboramos um dispositivo para a recolha de narrativas e três protocolos de entrevista clínico-dialógica, apropriados a cada um desses três atores.Com o objetivo de apreender o discurso sobre a vulnerabilidade das crianças que enfrentam dificuldades escolares, a abordagem é igualmente crítica, na medida em que apresenta uma interação dialética entre investigadores e participantes, em que os primeiros questionam os segundos, objetivando desvelar seus construtos com relação ao objeto de estudo.Essa proposta metodológica faz parte de um projeto de pesquisa que visa questionar fundamentos teóricos em função dos quais são conceitualizadas as dificuldades escolares -sociológica, pedagógica, médica, psicológica -com vistas a propor meios para agir em conjunto.

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)0.029
metaresearch head score (Gemma)0.045
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: Methods · Consensus signal: none
Teacher disagreement score0.029
Threshold uncertainty score0.155

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0290.045
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0150.008
Science and technology studies0.0100.029
Scholarly communication0.0160.016
Open science0.0040.012
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0030.001

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 head0.060
GPT teacher head0.368
Teacher spread0.308 · 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
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

Citations0
Published2020
Admission routes1
Has abstractyes

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