Exploring the Experiences and Perceptions of Early Childhood Educators in Ontario's Full-day Kindergarten Program
Bibliographic record
Abstract
Ontario’s Full-Day Kindergarten (FDK) educator team consists of an Early Childhood Educator (ECE) and an Ontario Certified Teacher (OCT). While the Ontario Ministry of Education (OME) describes this partnership as collaborative (e.g., Becker & Mastrangelo, 2017; OME, 2016; OME, 2022), others problematize the hierarchy and power dynamics in this relationship (e.g., Abawi, 2021a; Langford et al., 2016). This study uses intersectionality, gender, and critical race theories to explore how five ECEs’ identities shape their experiences in FDK. Findings suggest that a hierarchical dynamic exists, and cannot be considered in isolation of ECEs’ gender, race/ethnicity, and age. Hegemonic perceptions about Ontario ECEs are observed across six mediating spaces (kindergarten teacher, students, parents/caregivers, school community, administration, and board/ministry) that influence ECEs’ experiences. For students to benefit from the ECE-OCT union, educators, administrators, and policymakers must engage in self-reflective practice to become cognizant of their roles in influencing the challenges experienced by ECEs.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| 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".