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Record W4388568428 · doi:10.1590/0102-469839619-t

CONQUERING HEARTS AND MINDS: SOCIAL AND EMOTIONAL COMPETENCIES AS A REFLECTION OF NEOLIBERAL RATIONALITY IN LIFE PROJECT TEACHING TEXTBOOK

2023· article· en· W4388568428 on OpenAlexaboutno aff
Francisco Vieira da Silva

Bibliographic record

VenueEducação em Revista · 2023
Typearticle
Languageen
FieldPsychology
TopicPsychology and Mental Health
Canadian institutionsnot available
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsRationalityNeoliberalism (international relations)SociologyAutonomyPedagogyOrder (exchange)EpistemologyPsychologySocial sciencePolitical scienceLawPhilosophy

Abstract

fetched live from OpenAlex

ABSTRACT: This text aims at analyzing didactic collection (textbooks) entitled Life Project, in order to study how social-emotional competencies are addressed in such teaching materials and how they reflect the desires of neoliberal rationality. We search for theoretical support in studies developed especially in the reflections initially developed by Foucault (2008), later expanded by Dardot and Laval (2016) about neoliberalism.In what is concerned to methodology, it should be emphasized that this is a descriptive-interpretative study of documentary nature, following mainly a qualitative approach. The corpus is formed by fragments extracted from three teaching book collections entitled Life Project, books approved by the National Book and Teaching Material Program (PNLD), 2021 edition. Through the analysis, it can be considered that there is a direct relationship between social emotional competencies and neoliberal rationality, because young people are guided to regulate their emotions in order to improve their human capital and, as a corollary, they build their life project based on what is desirable at the core of a rationality nuanced by competition, individuality, resilience and autonomy.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.407
Threshold uncertainty score0.418

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.102
GPT teacher head0.445
Teacher spread0.343 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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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