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Record W4404737929 · doi:10.22215/cjcr.v11i1.4816

Reconceptualizing Early Childhood Educators as Champions for Children’s Rights: Introduction of the Children's Rights Advancement Framework

2024· article· en· W4404737929 on OpenAlexaffvenue
Emmie Henderson-Dekort

Bibliographic record

VenueCanadian Journal of Children s Rights / Revue canadienne des droits des enfants · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsMount Royal University
Fundersnot available
KeywordsEarly childhoodPolitical scienceChild rightsSociologyDevelopmental psychologyPsychologyHuman rightsLaw

Abstract

fetched live from OpenAlex

This article aims to further the representation of children's rights in literature and practice of Early Childhood Education (ECE) and introduces the Children's Rights Advancement Framework (CRAF). Despite theoretical alignment between the United Nations Convention on the Rights of the Child (UNCRC) and ECE policies, practical implementation and actualization remains elusive. During a conference presentation the authors of the article discovered through an anonymous survey that nearly 80% of the attendees, Early Childhood Educators, had little knowledge of UNCRC and its articles. Inspired by the work of the late Landon Pearson, an advocate for the rights of children, this paper critically reviews existing literature, identifies barriers to implementation in the Early Learning field, and introduces the CRAF as a transformative model. Drawing on a rights-based approach, the CRAF includes stages of conceptualization, implementation, application, and actualization of children's rights. The article emphasizes the need for awareness, education, and scaffolding knowledge of rights for both educators and children. The article highlights the transformative potential of the CRAF and offers practical implications and policy recommendations for advancing children's rights in ECE.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.586
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.254
Teacher spread0.246 · 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.

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
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Children s Rights / Revue canadienne des droits des enfantsSame topicEarly Childhood Education and DevelopmentFrench-language works237,207