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Record W4289766514 · doi:10.1177/20436106221117563

Against the self-regulated child: Early childhood pedagogies in neoliberal times

2022· article· en· W4289766514 on OpenAlexaffabout
Claudia Díaz-Díaz

Bibliographic record

VenueGlobal Studies of Childhood · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsSociologyEarly childhood educationAutonomyRationalityNeoliberalism (international relations)Context (archaeology)CurriculumColonialismPedagogyEarly childhoodSocial sciencePsychologyPolitical scienceDevelopmental psychologyLaw

Abstract

fetched live from OpenAlex

This article examines the curriculum and pedagogies for ethical practice in a childcare centre in Vancouver, Canada. I draw on Smith’s new model of childhood to examine narratives and practices around the ‘responsible child’ in a context where child developmental theories continue to influence pedagogical decisions. I argue that the elevation of self-regulation strategies as a pedagogical approach narrows children’s sense of responsibility to a mere individual trait. In addition, it fails to cultivate children’s interdependence and multiple relationships with humans and more-than-human others. Self-regulation-centred pedagogies also reinforce neoliberal and colonial discourses of the child anchored in human exceptionality, choice, autonomy and rationality. This article proposes that pre-service and in-service early childhood education needs to support educators in doing the analytical, embodied and reflective work to shift from educational paradigms founded in neoliberal and colonial rationalities towards an ethic that acknowledges children and educators’ interdependence and that cultivates good relations with humans and more-than-human others.

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)0.007
metaresearch head score (Gemma)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.237
Threshold uncertainty score0.472

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0200.068
Scholarly communication0.0090.004
Open science0.0010.009
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.299
Teacher spread0.284 · 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

Citations17
Published2022
Admission routes2
Has abstractyes

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