Merging the local and the global: a thematic analysis of rights-based picture books to facilitate a critical understanding of diverse childhood contexts in Ontario elementary school settings
Bibliographic record
Abstract
This study examines the importance of explicitly introducing children's rights in elementary educational classrooms in Ontario through the medium of rights-based picture books. Children's rights as framed within the United Nations Convention on the Rights of the Child (UNCRC) has been largely criticized for promoting a Western model of childhood, characteristic of innocence, play, and adult protection. Specifically, the UNCRC is often problematized for not capturing the diversity of childhoods that exist around the globe, as the articles in the Convention may not holistically examine the historical, cultural, and economic variables that children encompass. It is argued in this major research paper (MRP) that despite the limitations of the UNCRC, there is still a need to move beyond the universalism-cultural relativism dichotomy that currently frames this debate surrounding children's rights. Through a thematic analysis of selected rights-based picture books presented in the Elementary Teachers' Federation of Ontario‟s (ETFO) (2011) Social Justice Begins with Me resource kit, this MRP will explore how picture books related to the UNCRC can be a tool in classrooms to destabilize assumptions present between and within Majority and Minority World contexts and encourage pluralistic worldviews where diverse childhoods are actively accepted rather than stereotypically rejected.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.011 | 0.021 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".