The Substance Abuse Program for African-Canadian and Caribbean Youth (SAPACCY): An Innovative Program Serving the Mental Health Needs of African, Caribbean, and Black Youth
Bibliographic record
Abstract
Black youth experience disproportionately poor health outcomes throughout Ontario's healthcare system, including the mental health and addictions system. The Substance Abuse Program for African Canadian and Caribbean Youth (SAPACCY) at the Centre for Addiction and Mental Health (CAMH) seeks to address this disparity by providing clinical services to youth who identify as Black and/or as having African and/or Caribbean heritage, and their families, who are struggling with problematic substance use and/or mental health concerns. The clinical team works from an Afrocentric, culturally responsive lens to promote recovery and support Black youth in working through their mental health and addiction concerns. The program offers mental health and addictions counselling and psychotherapy, psychiatric consultation, psychoeducation, resource navigation, advocacy, and case management services to assist youth and their families/caregivers in reducing harm, moving toward recovery, and making healthy choices for themselves and their family. This paper will discuss SAPACCY’s approach to helping clients build resilience and resistance to anti-Black racism.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 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".