Leading and Learning: Collaboration in rehabilitation services in Ontario schools
Bibliographic record
Abstract
This dissertation explores how Ontario's leaders in education, health and the community envision effective collaboration in rehabilitation services in schools. First, superintendents of special education from 15 District School Boards (DSBs), directors/managers of 14 Children’s Treatment Centres (CTCs) and seven Special Education Advisory Committees (SEAC) representatives participated in seven like-role focus groups. Subsequently, a mixed role focus group comprised of representatives of the seven previous groups validated the findings derived through thematic analysis. Findings indicated there was no common understanding of the purpose and mandate of the school-based rehabilitation program which hampered work of leaders from rehabilitation and education as partners in co-serving children with or at risk of disabilities and their families. Furthermore, findings suggested that effective collaboration should be an intentional and relational process that enables partners to work together as equals, assume a learning stance, align a shared vision, include parents as partners and be child/family focused, and close communication gaps. Skills and qualities of leaders important to effective collaboration were identified as well as the beliefs of belonging, inclusion and the primacy of needs of child and family. Education, health, and community leaders identified their desire for change in policies governing rehabilitation services, the need for provincial guidelines and standards for services as well as knowledge building to support evidence-based service delivery models. Following the qualitative study, I developed a briefing note for policy and program decisionmakers in the provincial government. Subsequent presentations to government leaders positioned the findings within aims of the ministries responsible for rehabilitation services in schools. The article, “Building Back Better, Together,” presented findings relevant to education leaders on the collaboration of DSBs and CTCs during the COVID-19 pandemic to support children with rehabilitation needs, highlighting the urgency of working with CTC partners to reduce growing waitlists for services. The practice-oriented implications of this dissertation pertain to leaders creating a shared vision for services with all partners and aligning policy and services in accordance with this vision. Implications for research include exploring how leaders define shared responsibility in rehabilitation services in schools to clarify expectations and roles of partners.
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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.041 | 0.010 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".