Examining the potential of a coordinated service delivery model in child welfare in Ontario, Canada: Critical role of Black voices
Bibliographic record
Abstract
• Service coordination in Ontario’s child welfare system is very fragmented. • Coordinated service delivery model seeks to deliver holistic client-centered care. • Potential of coordinated service delivery is overshadowed by systemic challenges. • Black youth with lived experience emphasize the need for trust in the system. • Trust-building is required before a coordinated service delivery model is adopted. Poor outcomes for Black children and youth in the child welfare system in Canada are well documented in existing literature. A lack of service coordination among service providers has been highlighted as one of the barriers faced by children, youth and families receiving child welfare services, specifically from Black communities. However, there is little research on service coordination challenges in child welfare in the Canadian context. This paper examines the challenges and opportunities of coordinated service delivery in Ontario’s child welfare system, with a particular focus on the experiences of Black youth. Methodologically, the study relies on the user-centered design approach and via a series of focus groups seeks input from Black youth with lived experience in the child welfare system to explore service delivery issues and develop potential policy solutions. We identify issues such as service fragmentation, untimely referrals, and pervasive mistrust within the child welfare system. These are further exacerbated by systemic racism and a lack of culturally appropriate services. We conclude that the development of the coordinated service delivery model should begin with trust-building initiatives aimed at increasing Black staff representation in the child welfare system and beyond, enhancing transparency and accountability, and ensuring continued engagement of Black communities in policy design.
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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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.044 | 0.012 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".