Deepening Inclusive and Community-Engaged Education in Three Schools: A Teachers' Resource
Bibliographic record
Abstract
In 2009 the Toronto District School Board (TDSB) initiated the Inclusive Schools three-year pilot project with the intent to engage teachers, teacher educators, students, parents, staff, and administrators in investigating and developing effective inclusive curriculum and instructional practices that could be implemented in classrooms and school-wide. In addition, the project aimed to identify practices and factors that contribute to improved student engagement and learning and that strengthen community connections. Over a three-year period, three TDSB elementary schools - Carleton Village Public School, Flemington Public School, and Grey Owl Junior Public School - carried out 19 school-based inquiries. School-based inquiries were grounded in a professional learning process that emphasized inquiry, partnership, collaboration, action and reflection, and professional choice and responsibility. Participants had different understandings and experiences, which they brought to their particular investigations. This teachers’ resource contains reports on school-based inquiries into effective inclusive curriculum practices. It is intended for teachers who are considering the integration of inclusive approaches in their day-to-day work in schools. As such, the purpose of this resource is to contribute toward understanding how to support student learning and ongoing teacher education in ways that are responsive to today’s educational context.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".