Post-Secondary Education and the Full Integration of Government-Assisted Refugees in Canada: A Direction for Program Innovation
Bibliographic record
Abstract
Abstract Canada’s immigration goals are multifaceted and ambitious, reflecting both a desire to attract those who can contribute economically and culturally and offer protection to the displaced and the persecuted. Alongside these goals is a pledge that newcomers will receive the services and supports they need to fully integrate into Canada’s cultural and economic landscape. This chapter argues that post-secondary institutions, working in partnership with community organizations and primary/secondary schools, are well positioned to facilitate economic and cultural integration, particularly for otherwise vulnerable refugee groups. However, the authors’ previous research illustrates the many barriers refugee youth face in accessing Canadian post-secondary education. The authors hypothesize that efforts to increase post-secondary access – and, thereby, facilitate the accomplishment of immigration goals – will be most effective when specific age groups within the refugee demographic are targeted; in particular, younger children who have spent more time in the Canadian education system. This approach requires a shift in settlement practice from that of meeting only initial, urgent settlement needs, to one that enables the development of economic and cultural capacity. The authors envision a program that, on the one hand, helps refugees to value and gain the broad benefits of post-secondary education, while, on the other hand, directs post-secondary institutions to offer programs and pathways that are more inclusive to the unique challenges faced by this vulnerable demographic.
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.004 | 0.006 |
| 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".