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Bem-estar na escola e percepção da discriminação de gênero por meninas

2023· article· pt· W4386324266 on OpenAlexaff
Benedito Rodrigues dos Santos, Lêda Gonçalves de Freitas, Nair Cristina da Silva Tuboiti

Bibliographic record

VenuePsicologia da Educação · 2023
Typearticle
Languagept
FieldSocial Sciences
TopicPoverty, Education, and Child Welfare
Canadian institutionsInternational Institute for Child Rights and Development
Fundersnot available
KeywordsHumanitiesPsychologySociologyPhilosophy

Abstract

fetched live from OpenAlex

Este artigo analisa, a partir da pesquisa “Ser Menina no Brasil”, o bem-estar na escola e a (pouca) percepção da discriminação de gênero por meninas de 6 a 14 anos. Foram utilizados os dados quantitativos da Amostra-Escola, que envolve 1.609 meninas, de 21 municípios brasileiros, referente à dimensão “Escola e Escolarização” e que aponta a percepção das meninas sobre a frequência às aulas, os motivos de faltar à escola, os níveis de aprovação e reprovação, a interrupção dos estudos, os motivos de expulsão, as tarefas escolares, as relações de gênero no contexto escolar e a satisfação e bem-estar na escola. A análise indicou uma percepção favorável ao bem-estar na escola e relações de gênero benéficas para as meninas. Estudos assim devem focar o contexto educativo, o qual possibilita a inserção e a construção de um lugar de pertencimento e a ruptura com uma cultura de desigualdade social que ainda mascara a exclusão.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, 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 score0.319
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.003

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 head0.063
GPT teacher head0.347
Teacher spread0.283 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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