Asylum and resettlement in Canada. Historical development, successes, challenges, and lessons
Bibliographic record
Abstract
By the year 2020, there were more than 280 million international migrants across the globe. Of this figure, 26.4 million were refugees, who have fled for a variety of reasons, including persecution, violence and human rights violations. Canada is considered the world leader in the protection of refugees. Notwithstanding this generally positive perception, the Canadian protection system exhibits a series of deficiencies, ranging from detention policies and deportation in the case of asylum seekers, down to the integration obstacles and other associated challenges encountered by resettled refugees. In addition, other challenges including violence, vulnerability, denial of rights, and growing hostility toward migrants and refugees undermine the overall health and image of the system. This book is a project aimed at addressing this topic and the challenges associated with it. More specifically, the overall goal of it is to provide readers with an in-depth account of Canada’s refugee protection programs, their origins and development, their achievements, challenges and metamorphoses, with a particular accent given to the role of community involvement in these programs. It is intended to offer a comprehensive and a thorough account of the entire system and of the role of community engagement in its success and refinement.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.019 | 0.007 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".