Early childhood educators’ experiences implementating a social competence promotion program for preschool-aged children : the "safe spaces" program
Bibliographic record
Abstract
The primary aim of this research was to describe the implementation of the Safe Spaces program across child care settings. The Safe Spaces program is a universal primary preventive program designed to foster preschool-aged children's emotional and social competence via a series of lessons that teach children emotional understanding and prosocial behaviours. The program was piloted in one child care centre in 2001 and is currently being implemented in over 50 child care settings across British Columbia, Canada. Although the Safe Spaces program has anecdotal evidence suggesting positive outcomes, little is known about whether or not the program is being implemented as intended across different child care settings and how child care centre characteristics, including early childhood educators' beliefs and experiences, might influence program implementation. Accordingly, 10 Early Childhood Educators (ECEs) drawn from five child care centres implementing the Safe Spaces program were asked to provide information via a series of questionnaires, interviews, and implementation record logs about the implementation of the Safe Spaces program in each of their centres. Results revealed high implementation (i.e., program adherence, extent to which specific program components are delivered as prescribed in program manuals and dosage, the frequency with which program techniques are implemented) of the Safe Spaces program across centres. Despite these reports, educators revealed that centre, child, and implementers' characteristics were related to the adoption and implementation of the program. Challenges and successes help identify recommendations for future implementation.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".