Decolonial Education through Solidarities: Anti-Racism Learning in Early Childhood Education And Care in Canada
Bibliographic record
Abstract
This chapter explores the transformative potential of decolonial education within the context of early childhood education and care (ECEC) in Canada, focusing on antiracism learning. Grounded in critical pedagogy and decolonial theory, the study examines how solidarity-based approaches can foster inclusive and equitable educational environments for young children. By analyzing current practices and policies, as well as drawing on case studies and qualitative data, the research highlights the complexities and challenges of implementing antiracist education in ECEC settings. Moreover, it underscores the importance of solidarity among educators, families, and communities in dismantling colonial legacies and promoting social justice. This study contributes to ongoing discussions in educational theory and practice by advocating for decolonial approaches that center Indigenous knowledges and perspectives, aiming to empower young children and foster a more just society.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.029 | 0.011 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".