Equity as Praxis in Early Childhood Education and Care
Bibliographic record
Abstract
Equity as Praxis in Early Childhood Education and Care aims to map, deconstruct, and engage with different models of equity as they pertain to the early childhood education landscape in Ontario. Drawing on marginalized narratives of gender, race, Indigeneity, dis/ability and inclusion, and migration, immigration, and displacement, the authors discuss how to advance the field and make it more equitable for children, families, early childhood educators, and all other practitioners. This edited collection outlines the current political climate of early childhood education and care in Ontario through a critical analysis of policies and dominant discourses of equity and inclusion. By prompting readers to reflect on and critique their understandings of children, families, communities, and practices in the field, the authors seek to provide counternarratives to Eurocentric developmentalist hegemonies and an alternative strength-based approach to critical and transformative praxis. This vital text encourages rethinking how narratives of equity and inclusion are constructed and what this means for young children and their families in Ontario, as well as throughout Canada. This is an essential resource for students in early childhood education and care, early childhood studies, and education programs.
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 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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.020 | 0.048 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".