The Development of a Social Work Program for an Islamic Day School in Southwestern Ontario
Bibliographic record
Abstract
The Development of a Social Work Program for an Islamic Day School in Southwestern Ontario Abstract This article examines the evolution of a social work program for an Islamic Day School in London, Ontario, Canada. The Muslim Resource Centre for Social Support and Integration (MRCSSI), and London Islamic School (LIS) developed A Safe Space for Children (SPC) school social work program after extensive community consultation and feedback from leadership and school teachers revealed the need for mental health supports for students. A program implementation and evaluation design was developed by the MRCSSI in collaboration with the LIS and accepted by school administration and community stakeholders. The overarching objectives were to provide students with counselling services; develop school wide interventions, connect students and their families to mental health community resources while also providing ongoing professional development opportunities to teachers on issues relating to student mental health issues. The development of SPC its rooted in literature that reveals that this population is vulnerable to the stigma related to mental health, issues of acculturation, racism, and discrimination. The establishment of a social work program situated in a faith-based school that offers an overall understanding of cultural values and spirituality, aligns with best practices in social work. The project was grounded in a participatory democracy approach integrated with the civil society perspective, constructivist and critical race theoretical frameworks that guided the assessment and program design. Key Words: Canada, Children, Islam, Mental Health, Muslim, Participatory Democracy, School Social Work
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".