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Record W7133021087

Addressing Complexities in Early Childhood Education and Care: The Relationships among Paradigms, Policies, and Children's Rights to Participate

2017· dissertation· W7133021087 on OpenAlexafffund
Darya Dasha Shalima

Bibliographic record

VenueTSpace · 2017
Typedissertation
Language
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsUniversity of Toronto
FundersMacEwan UniversityStrong
KeywordsEarly childhood educationEarly childhoodArgument (complex analysis)Field (mathematics)Empirical researchCritical theoryEmpirical evidenceChildhood studies
DOInot available

Abstract

fetched live from OpenAlex

This dissertation contributes to the field of Early Childhood Education and Care studies by providing the in-depth theoretical, document, and empirical analyses. The three types of analysis aim to build a case for the practical utilization of the critical paradigm. The critical paradigm is understood as a driving force for early childhood pedagogy which empowers educators, policy-makers, and academic scholars to apply a practical change in the field while acknowledging and sustaining the young childrenâ s right to actively participate in matters related to their education and well-being. In this venue, the thesis provides (i) a thorough and productive analysis of the paradigmatic discussions presently available in the field of early childhood education; (ii) an argument for the practical application of the critical paradigm; (iii) an application of the paradigmatic debates to early childhood curricular and policy documents; (iv) and an empirical evidence from the field which has not been documented before and which gives insights to changes needed in policy directions and the preparation of pre-service early childhood educators.

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)0.040
metaresearch head score (Gemma)0.053
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 score0.040
Threshold uncertainty score0.210

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0400.053
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0120.057
Scholarly communication0.0190.014
Open science0.0020.017
Research integrity0.0040.010
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 head0.106
GPT teacher head0.412
Teacher spread0.306 · 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

Citations0
Published2017
Admission routes2
Has abstractyes

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