Mental health literacy in Nova Scotia’s education system: 15 years after the evergreen framework
Bibliographic record
Abstract
This study examined the current state of mental health literacy (MHL)-related educator training, certification, and policy in Nova Scotia, Canada. It addressed three research questions: (i) How has Nova Scotia's educational policy landscape responded to the Evergreen Framework's (EF's) strategic directions? (ii) What are the strengths and gaps in current MHL-related policies? (iii) What sources of MHL training are available to preservice educators through Bachelor of Education (B.Ed.) and early childhood education (ECE) programs and to in-service educators through Master of Education (M.Ed.) programs and professional development (PD). A deductive content analysis was used to evaluate the alignment of provincial policies with the EF. An environmental scan and systematic analysis were conducted across ECE, B.Ed., and M.Ed. programs, as well as PD offerings and curriculum content. Findings indicate that while aspects of MHL are embedded within inclusive education policies and select course offerings, explicit training in MHL is limited and inconsistently implemented. PD opportunities and regional education center resources vary widely, and MHL competencies are not mandated for certification. The study provides recommendations for policy and training reform.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 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".