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Record W2113172831 · doi:10.2304/ciec.2010.11.1.113

Critiquing Child-Centred Pedagogy to Bring Children and Early Childhood Educators into the Centre of a Democratic Pedagogy

2010· article· en· W2113172831 on OpenAlexaff
Rachel Langford

Bibliographic record

VenueContemporary Issues in Early Childhood · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsEarly childhood educationPedagogySociologyEarly childhoodConstruct (python library)Gender studiesCritical pedagogyFace (sociological concept)Teacher educationDemocracyPsychologyPolitical scienceSocial scienceDevelopmental psychologyPolitics

Abstract

fetched live from OpenAlex

Child-centred pedagogy is both an enduring approach and a revered concept in Western-based teacher preparation. This article weaves together major critiques of child-centred pedagogy that draw on critical feminist, postmodernist and post-structural theories. These critiques have particular relevance for conceptualizing what it can mean to be, and what it takes to become, an early childhood professional. The construct of the female early childhood professional is particularly important with the current intensification of the teacher as a technician and the increasing numbers in the workforce from racialized groups who may face social inequities. The construction of the individualized child and its parallel denial of the influences of gender, ethnicity and class on who a child becomes are equally important. Drawing upon the work of reconceptualist scholars, some preliminary ways will be proposed in which we can theorize and reconstruct children and early childhood professionals at the centre of a pedagogy that is a democratic space for all.

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)0.041
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.041
Threshold uncertainty score0.218

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0410.022
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0130.120
Scholarly communication0.0180.014
Open science0.0030.012
Research integrity0.0080.015
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 head0.011
GPT teacher head0.306
Teacher spread0.294 · 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

Citations136
Published2010
Admission routes1
Has abstractyes

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