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Record W4362635274 · doi:10.32920/22557550

Through the Lens of Children's Rights: A Discourse Analysis of Popular Children's Literature

2023· preprint· en· W4362635274 on OpenAlexaff
Bethany Robichaud

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldHealth Professions
TopicDigital Storytelling and Education
Canadian institutionsEducation and Early Childhood DevelopmentToronto Metropolitan UniversityUniversity of Prince Edward Island
Fundersnot available
KeywordsConvention on the Rights of the ChildNarrativeReading (process)ConventionPolitical scienceChild rightsPsychologyHuman rightsLawLiteratureArt

Abstract

fetched live from OpenAlex

Adopted in 1989, the United Nations Convention on the Rights of the Child (UNCRC) delineates the inherent, equal, and indivisible rights that all children hold. However, almost 30 years after the establishment of the UNCRC, there is still a lack of awareness of children’s rights. Through the lens of children’s right, this study examined if, how, and to what extent children’s rights are communicated in the lexical and pictorial narratives of ten popular preschool children’s storybooks. Findings show that although children’s rights discourses are plentiful in varying degrees in children’s storybooks, these discourses are primarily implicit. Implications from this study suggest that early childhood educators may adopt a “right-integrative” (Di Santo & Kenneally, 2014, p. 396) lens when selecting, reading, and discussing storybooks with young children, with an aim to increase awareness of rights. Keywords: children’s rights; children’s literature; United Nations Convention on the Rights of the Child

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)0.006
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.005
Science and technology studies0.0070.024
Scholarly communication0.0100.011
Open science0.0010.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.052
GPT teacher head0.397
Teacher spread0.346 · 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 designQualitative
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

Citations1
Published2023
Admission routes1
Has abstractyes

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Same topicDigital Storytelling and EducationFrench-language works237,207