The Implementation of Suspension and Expulsion Programs in Two Ontario School Boards
Bibliographic record
Abstract
In 2008, the Ontario Ministry of Education made it mandatory that school boards in the province institute programs to serve suspended and expelled youth. These programs have now been in place for five years. Limited information has been collected as to how effective they are in addressing the needs of these students and little is known about the factors that have had an effect on the implementation of these policies. This study provides a description of the programs and focuses on the factors that have impacted policy implementation in this area. Research has shown that several factors impact policy implementation in general. Among the main influential factors are the impact of policy actors, the conditions that exist, supports that are available and the level and type of central control that is in place. Through one-on-one interviews involving thirteen school and board personnel in two Ontario school boards, this research explored how these four factors had an impact on the policy implementation process as it relates to the suspension and expulsion programs. The study participants believed that the relationships within and between these four factors and the creativity and flexibility this allowed were important in their ability to implement the new policies. Collaborative relationships between school board personnel and their community partners were highlighted in both participating boards as encouraging policy implementation. Strong relationships between staff, the students, and their families were important in finding program solutions for the particular conditions that existed, especially in the rural board that participated in the study. The importance of strong relationships between board personnel and community partners was also stressed, especially in the board that had a combined urban and rural make-up. Two-way communication between board and Ministry personnel allowed for the provision of appropriate supports in order to keep the programs viable. I conclude that when it comes to implementing new policies, central control from the Ministry should demonstrate an understanding of the distinct situations that exist in each board, the importance of key relationships, and the need for flexibility in allowing for creative responses to the needs that exist.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.019 | 0.006 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.004 |
| 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".