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Record W4229456573 · doi:10.1590/scielopreprints.4090

CONQUISTANDO CORAÇÕES E MENTES: AS COMPETÊNCIAS SOCIOEMOCIONAIS COMO REFLEXO DA RACIONALIDADE NEOLIBERAL EM COLEÇÕES DIDÁTICAS DE PROJETO DE VIDA

2022· preprint· pt· W4229456573 on OpenAlexaboutno aff
Francisco Vieira da Silva

Bibliographic record

Venuenot available
Typepreprint
Languagept
FieldSocial Sciences
TopicDiverse Education Studies and Reforms
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhilosophySociology

Abstract

fetched live from OpenAlex

O objetivo deste texto consiste em analisar coleções didáticas de Projeto de Vida, com vistas a estudar como as competências socioemocionais são abordadas em tais materiais didáticos e de que forma refletem os anseios da racionalidade neoliberal. Para ancorar teoricamente o estudo, busca-se respaldo, sobretudo em Foucault (2008), em Dardot e Laval (2016), em Lemos e Macedo (2019), em Ciervo (2019), em Smolka et al (2015), dentre outros. Acerca da metodologia, convém frisar que se trata de um estudo descritivo-interpretativo de cunho documental, seguindo uma abordagem eminentemente qualitativa. O corpus é formado por fragmentos extraídos de três coleções didáticas de Projeto de Vida, aprovadas pelo Programa Nacional do Livro e do Material Didático (PNLD), edição de 2021. Por meio da análise, pode-se ponderar que há uma relação direta entre as competências socioemocionais e a racionalidade neoliberal, porque os jovens são orientados a regular suas emoções, com vistas a aperfeiçoar o capital humano e, como corolário, construir o projeto de vida com base naquilo que é desejável no cerne de uma racionalidade matizada pela concorrência, individualidade, resiliência e autonomia.

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)0.010
metaresearch head score (Gemma)0.022
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: Empirical · Consensus signal: none
Teacher disagreement score0.023
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.022
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.006
Science and technology studies0.0090.022
Scholarly communication0.0160.013
Open science0.0020.010
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0140.001

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 head0.069
GPT teacher head0.396
Teacher spread0.327 · 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
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
Published2022
Admission routes1
Has abstractyes

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