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Record W4387934910 · doi:10.55905/revconv.16n.10-245

O ensino de sociologia no ensino básico brasileiro: a contribuição de Florestan Fernandes e outros sociólogos

2023· article· pt· W4387934910 on OpenAlexaff
Raimundo Paulino Da Silva, Lílian Almeida de Souza Cid

Bibliographic record

VenueContribuciones a las Ciencias Sociales · 2023
Typearticle
Languagept
FieldSocial Sciences
TopicSociology and Education in Brazil
Canadian institutionsGreo
Fundersnot available
KeywordsHumanitiesLogos Bible SoftwarePhilosophySociologyTheology

Abstract

fetched live from OpenAlex

Este estudo tem como objetivo apresentar, problematizar e refletir sobre o ensino de sociologia no ensino básico brasileiro a partir do pensamento do sociólogo Florestan Fernandes, articulado com o que pensa outros sociólogos que têm tal ensino como objeto de pesquisa. Trata-se de um estudo de pesquisa bibliográfica (GRESSLER, 2007), mas de forma problematizada teoricamente e, também, ancorada numa metodologia analítica (BECKER, 1999). A questão de pesquisa procura saber até que ponto as contribuições do referido sociólogo paulista foram importantes para se pensar o ensino de sociologia no ensino médio nestas últimas décadas, destacando estudos mais recentes que tratam dessa tão importante temática. Do diálogo com outros sociólogos, tais como Casão e Quinteiro (2007); Guelfi (2007); Sarandy (2007); Handfas e Teixeira (2007); Jinkings (2007); Silva (2007) entre outros, resultaram em reflexões que nos faz pensar um ensino de sociologia mais crítico, reflexivo, problematizador, mas não conclusivo. Da análise, entendemos que o ensino de sociologia no ensino médio brasileiro, a partir de Florestan, passa pela formação inicial do professor, atravessada pelas alternâncias em se tratando de sua obrigatoriedade e quando foi facultado e, também, pela relevância dessa disciplina, como sendo a mais viável para a compreensão dos temas da realidade social e de uma formação crítica.

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)0.003
metaresearch head score (Gemma)0.006
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.413
Threshold uncertainty score0.822

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.006
Science and technology studies0.0070.007
Scholarly communication0.0060.003
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.123
GPT teacher head0.387
Teacher spread0.264 · 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
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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