A Case for Using Indigenous Children's Literature for Emotion Socialization in Schools
Bibliographic record
Abstract
Building on the work of developmental theorists, this article argues that school is a significant cultural site for emotion socialization and that the use of cultural texts such as children's picture books can play an important role in helping young children to identify and express emotions, and learn about their relational context. The author takes the perspective that teaching and learning about emotions are never neutral; they are complex, dialectical and are freighted by history, relations of power and influenced by factors such as race, class, gender, and language. As a way of countering social devaluation, exclusion and omission, the article makes a case for using children's texts that feature the cultural and family contexts of indigenous groups such as the Métis of Canada. It shows how culturally relevant and developmentally appropriate picture books that are rich with emotion-related themes and vocabulary can be used in schools to teach about the cultural and family contexts of emotion socialization.
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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 | 0.014 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.020 | 0.062 |
| Scholarly communication | 0.012 | 0.014 |
| Open science | 0.003 | 0.016 |
| Research integrity | 0.004 | 0.007 |
| 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".