Identifying Mental Health Initiatives for Independently Funded Christian Elementary Schools in Ontario
Bibliographic record
Abstract
This study seeks to understand the use of mental health strategies within independently funded Christian elementary Schools (IFCES), while considering how research literature identifies the implementation of mental health strategies in publicly funded elementary schools. There is a major research gap for IFCES in this area. This study used a qualitative approach via structured interviews to gather data reflecting how IFCES provide mental health supports. A wide variety of programming and supports within the schools (both IFECS and publicly funded) were identified during the research process. While the tiered system of support has been strongly considered in research literature (Sanchez, Cornacchio, Poznanski, Golik, Chou, & Comer, 2018), the IFECS sector did not intentionally use this framework as a support to implement a mental health plan. This study identified that IFECS are gaining momentum in mental health programming and would benefit further from utilizing a framework to address their growing mental health needs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".