Education for Young Refugees : Processes of Inclusion and Exclusion in Munich and Toronto
Bibliographic record
Abstract
Featuring leading voices in the field from across Canada and Europe, this edited collection offers empirical analyses of the historical, social, cultural, and legislative determinants of inclusive education in Canadian schools. \n \nCovering four thematic areas including the structure, culture, and practices of inclusive education, the volume offers comparative insights from a European perspective, engaging critically with widely held views of Canada as a world leader in inclusive education. Providing rich comparisons with educational systems in Germany, Spain, and Finland, chapters explore in-depth the assessment structures and curricula specific to Canada, as well as educational policy, and explore attitudes and practices in relation to diverse student populations, including refugee and indigenous peoples, and students with special educational needs. \n \nThis volume will benefit researchers, academics, and educators with an interest in multicultural education, international and comparative education, as well as educational policy more specifically. Those involved with inclusion and special educational needs will also benefit from this volume.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.034 | 0.016 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".