Troubling Signs: Mapping Access to Justice in Canada's Refugee System Reform
Bibliographic record
Abstract
In 2012, Canada’s refugee system underwent a significant transformation. Throughout the period of reform, refugee advocates, researchers and support workers expressed concern that the changes would individually and cumulatively exacerbate existing access to justice deficits for refugee claimants. Drawing on experience from the authors’ involvement with the University of Ottawa Refugee Assistance Project, as well as dedicated supplementary research, this paper begins by outlining a social context conception of access to justice and then explores how access to justice issues were considered as part of the refugee system reform process, including what deficits experts foresaw arising as a result of that reform. The paper then details institutional responses to the new system, before providing insights on the access to justice deficits experts indicated refugees were actually experiencing two years after implementation of key reforms. This analysis draws on a variety of primary and secondary sources, including an actual claimant file which is used to both explore key access to justice concerns and illustrate the vital importance of more in-depth study in this area.
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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.012 |
| Science and technology studies | 0.021 | 0.010 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".