A study of the reform process to provide an inclusive model of service delivery within a Manitoba middle years school
Bibliographic record
Abstract
Several current social agendas in the province of Manitoba are impacting the demographics in our classrooms. Recent changes to the Public Schools Act, the Educational Administration Act, an aggressive immigration initiative and a trend for movement from rural to urban settings have contributed to classrooms where the learning and behaving needs of students are diverse, their motivations to learn are different and they have varied areas of strength and weakness. In order to meet these new challenges and to provide educational programming that reflects the needs of our global society, schools need to change the way they are delivering service to students in schools. This study used qualitative research methods to examine the conditions that facilitate building an inclusive middle school in Manitoba. Data from both focus group interviews and a document study yielded multiple themes under the headings of actions, culture and strategies. A historical scan of the school’s reform process highlighting the changes in beliefs, leadership, structures and processes over time resulted from the data analysis. Collectively, the findings identify the specific steps the school took to move to inclusion. The information contained in this study will provide a path to help educators move to creating inclusive school environments where all students feel a sense of belonging and fulfillment from their educational experiences.
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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.034 | 0.013 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".