Fostering Synergy: Enhancing Children and Youth Outcomes through Collaboration Across Human Service Organizations- Insights from TRiP (The Regina intersectoral Partnership)
Bibliographic record
Abstract
Access to services and supports for children and youth in vulnerable contexts remains a key challenge in Canada due to fragmented service delivery systems. Cross-sectoral collaboration has proven to be an effective strategy to overcome existing silos through providing wraparound coordinated services, and a means to promote healthy development and safety of children. Given the challenges associated with establishing and sustaining cross-sector collaborations, including coordination issues and conflicting interests of the sectors involved, our study used TRiP (The Regina intersectoral Partnership) as a case study to explore the dynamics of this collaborative initiative. TRiP is a collaboration across six human service organizations to improve outcomes for children/youth in vulnerable contexts, which has been functioning in Regina, Saskatchewan since 2010. Our research aimed to investigate the emergence, formation, and evolution of this cross-sectoral collaboration; factors influencing collaboration and service coordination across sectors; and the processes and structures involved in establishing and sustaining robust collaborative initiatives. By drawing on interviews with stakeholders from six human service organizations engaged with TRiP (n=25), and persons with lived experience (n=20), observations, and document reviews, the research team identified factors influencing collaboration and service coordination across sectors. We also examined the governance, process of coordinating services across sectors, funding structure, and accountability mecha¬nisms within TRiP. Our research findings are categorized into four key themes: 1) achievements and outcomes, 2) factors contributing to success and sustainability, 3) perceived gaps and areas for improvement, and 4) suggestions for improvement. Many caregivers and children interviewees pointed to the significant achievements and outcomes accomplished by TRiP since its conception, including: the positive outcomes to the safety and well-being of children; and the positive outcomes experienced by the caregivers, including a nurturing support, improved child-caregiver relationships, and better access to support services. Participants identified a host of factors contributing to the success and sustainability of TRiP including: having a shared vision to guide the direction of TRiP; continuous growth and evolution of the initiative; the leading role of champions within the initiative; the sharing of information between sectors and stakeholders; having a dedicated and single point of contact between TRiP and its clients; and TRiP’s ability to act as a conduit for effectively communicating with various human services organizations. Participants also identified several areas for improvement within TRiP, including: chronic resource limitations; administrative hurdles associated with information sharing; ongoing siloing of sectors engaged; TRiP’s limited public presence; and limitations to clients in the form of age-restricted supports and disrupted continuity of care. Finally, participants provided suggestions for improvement to guide the continued refinement and evolution of TRiP, including: adoption of a proactive rather than reactive approach; enhancement of TRiP’s visibility in the public; revitalization of TRiP’s current system of governance; strengthening TRiP’s accountability mechanisms; establishing cohesive and unified definitions and measures of success; enhancing staff retention; and expanding the range of support opportunities for children.
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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 | 0.015 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.010 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.002 | 0.024 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".