Keeping the lamp lit: A program profile of a community-based social-emotional training for caregivers and educators
Bibliographic record
Abstract
Developing social-emotional training opportunities for caregivers and professionals can promote higher quality care for children and families in the home and in early years services. Community-based efforts that integrate developmental-relational research into practice using a participatory approach are a growing area of interest and focus. The current paper provides a program profile of RAISE (Research and Practice Partnership: Building Awareness and Increasing Social-Emotional Capacity in the Early Years), a social-emotional training model that uses a bottom-up community-based approach to design and implement a developmental-relational training to strengthen caregivers’ and educators’ capacities to support children’s social-emotional development and mental health. We describe our training development approach, which integrates community engagement efforts with developmental-relational and clinical research, including examples of how participatory approaches may inform curricula development. Finally, we highlight several lessons learned from this training model, with the aim of informing future social-emotional development and practice initiatives.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".