Towards Equitable Inclusion for Refugees: The Needs of Students With and Seeking Refugee Protection
Bibliographic record
Abstract
Despite data increasingly being used to advance equity in education, students with and seeking refugee protection (SWSRP) are largely invisible in education data. To equitably include SWSRP in national education systems as envisioned by global refugee education policy, data on their needs are required. The purpose of this study was to source, organize, and analyze data on the needs of SWSRP in primary and secondary education in Canada. This needs assessment involved the use of experts, a selective review of empirical literature, and a review of publicly available data. Five common areas of need were identified among SWSRP globally and across Canada’s 13 primary and secondary education systems: access to education, accelerated education, language education, mental health and psychosocial support, and special education. Rates of needs varied by a range of student experiences and circumstances. These data can inform efforts to responsively support SWSRP in Canadian education systems.
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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 | 0.016 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.015 | 0.007 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".