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Record W4390466670 · doi:10.26694/rles.v27i55.4671

POLÍTICAS EDUCACIONAIS NEOLIBERAIS E AVALIAÇÃO EXTERNA: EXPERIÊNCIAS DO SAERS EM ESCOLAS PÚBLICAS DE RIO GRANDE

2023· article· pt· W4390466670 on OpenAlexaboutno aff
Magda de Abreu Vicente, Juliana Silveira Oliveira

Bibliographic record

VenueLinguagens Educação e Sociedade · 2023
Typearticle
Languagept
FieldSocial Sciences
TopicEducation Pedagogy and Practices
Canadian institutionsnot available
FundersFundação de Amparo à Pesquisa do Estado do Rio Grande do Sul
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

A presente pesquisa, de cunho qualitativo, tem como objetivo investigar os reflexos da aplicação do Sistema de Avaliação de Rendimento Escolar do Rio Grande do Sul (SAERS) em seis escolas públicas do município de Rio Grande, no estado do Rio Grande do Sul. Para tanto, contou com suporte metodológico da Análise Temática Reflexiva (ATR) orientada pelos estudos de Marques e Graeff (2022) e Souza (2019). Os dados foram produzidos entre os meses de dezembro de 2022 a março de 2023, através de questionários compostos por seis perguntas, que foram respondidas por escrito por 12 professoras de 2º e 5º ano do Ensino Fundamental. Realizou-se, também, uma análise documental do Decreto nº 56.679 que instituiu o SAERS. O referencial teórico baseou-se, principalmente, em Afonso (2013), Harvey (2014) e Laval (2004) que auxiliaram na análise do contexto neoliberal das atuais políticas públicas de avaliação. Como resultado mais evidente foi possível perceber impactos da prova para discentes e docentes, seja porque interferiram na prática docente ou porque abalaram psicologicamente os discentes envolvidos.

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)0.003
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.200
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0040.001
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0160.006

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 head0.082
GPT teacher head0.431
Teacher spread0.349 · 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 designQualitative
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

Citations1
Published2023
Admission routes1
Has abstractyes

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