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Record W3126333324 · doi:10.37885/201202613

UMA BREVE ANÁLISE DAS MUDANÇAS NA POLÍTICA PÚBLICA DA EDUCAÇÃO ESCOLAR BRASILEIRA A PARTIR DA CRÍTICA DE DARDOT E LAVAL:

2021· book-chapter· pt· W3126333324 on OpenAlexaboutno aff
Erika Mara Nogueira de Santana Ticle, Larissa Figueiredo Salmen Seixlack Bulhões, Gustavo Costa de Souza

Bibliographic record

VenueEditora Científica Digital eBooks · 2021
Typebook-chapter
Languagept
FieldSocial Sciences
TopicEducation Pedagogy and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

O presente estudo pretende demonstrar a relevância da compreensão das interferências neoliberais em instrumentos de organização educacional, interferências estas promovidas através de bases curriculares unificadoras de conteúdos, fundamentadas na concepção pedagógica construtivista. Para tanto, utilizamos uma abordagem de revisão de literatura, a partir da obra de Dardot e Laval (2016) e da crítica sobre as influências neoliberais sobre as reformas curriculares da Nova Zelândia, ocorridas em 2007. Da análise observa-se a adesão da política pública da educação básica brasileira na ordem neoliberal internacional a partir da implementação da Base Nacional Curricular Comum (BNCC). O estudo proporcionou ampliação do conhecimento teórico sobre o tema e um ponto de apoio para se observar, comparativamente, a mediação neoliberal no contexto educacional brasileiro, acompanhando uma tendência global observável em diversos países do mundo. A pesquisa contribui com estudos que buscam soluções aos problemas públicos da educação escolar brasileira, na compreensão do caminho adotado na implantação da BNCC brasileira, vinculada à racionalidade neoliberal e pode servir como estímulo à formulação de alternativas aos padrões neoliberais em nossas escolas.

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)0.005
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.341
Threshold uncertainty score0.679

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.009
Science and technology studies0.0060.007
Scholarly communication0.0080.003
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.000

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 head0.064
GPT teacher head0.367
Teacher spread0.304 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2021
Admission routes1
Has abstractyes

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