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Record W2960502313 · doi:10.1590/1981-7746-sol00223

TRABALHO, EDUCAÇÃO E JUVENTUDES: DIÁLOGO COM O PENSAMENTO SOCIAL DE CHRISTIAN LAVAL E PIERRE DARDOT

2019· article· pt· W2960502313 on OpenAlexaboutno aff
Roberto Rafael Dias da Silva

Bibliographic record

VenueTrabalho Educação e Saúde · 2019
Typearticle
Languagept
FieldArts and Humanities
TopicArts and Performance Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhilosophySociology

Abstract

fetched live from OpenAlex

Resumo O presente estudo teórico propõe um dia-gnóstico crítico das relações entre trabalho, educação e juventudes contemporâneas, por meio de um breve diálogo com o pensamento social de Christian Laval e Pierre Dardot. Sua preocupação central encontra-se na emergência de novos arranjos subjetivos no contexto do neoliberalismo. Para pensar tais relações foram considerados três traços conceituais derivados das obras dos autores selecionados: a compreensão da crise como modo de vida permanente, a ênfase nos aspectos emocionais e no dispositivo desempenho/gozo e a reinscrição da formação juvenil no território do comum. Ao longo do estudo, evidencia-se que um referencial analítico crítico e heterodoxo, sustentado numa releitura específica do pensamento de Marx articulada a outras contribuições, da forma como tratado por Dardot e Laval, apresenta potencialidade heurística significativa para pensar os conceitos de trabalho, educação e juventude no contexto brasileiro atual.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.038
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0120.023
Scholarly communication0.0070.003
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.035
GPT teacher head0.286
Teacher spread0.251 · 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 designTheoretical or conceptual
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

Citations2
Published2019
Admission routes1
Has abstractyes

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