Issues of Cost & Access in Canada’s Early Childhood Education System: Lessons for the Civil Justice System
Bibliographic record
Abstract
In recent years in Canada, there has been growing appreciation that early childhood education (ECE) is a basic foundation for building a successful education system, competitive global economy, and a well functioning democracy. A policy of publicly funding ECE programming is, in other words, seen as a smart investment in the future. This new appreciation of ECE is evident from the fact that ECE is now integrated into our school system and early childhood educators are recognized as trained professionals, not mere childcare workers. ECE policies in Ontario are now a model of evidence-based decision-making. Early learning initiatives such as full-day kindergartens and seamless days are based on new innovative research on child development that shows the long term benefits of skills such as early literacy and self-regulation for young children. ECE is also an effective compensatory vehicle for children from disadvantaged socio-economic backgrounds.
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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 | 0.007 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.017 | 0.010 |
| Scholarly communication | 0.019 | 0.007 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.019 | 0.001 |
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".