Bibliographic record
Abstract
This paper is the second in a series of papers on Canada’ asylum system. The first paper, Ping-pong Asylum, took us to the border, and outlined the issues behind the recent influx of people crossing there. This paper focuses on what happens to those people, and other asylum seekers, once they are inside Canada. The analysis shows that Canada’s asylum system is not an easy path to living in Canada or gaining citizenship. Asylum seekers or Canadian citizens who think asylum is a form of queue jumping or circumventing normal immigration pathways are mistaken. It is a complex web of agencies and steps. This complexity partially results from the due process granted to asylum seekers. It is also the result of evolving bureaucracies and case management systems impacted by political agendas and sudden surges in asylum seeker numbers. This complex system does not lend itself well to a quick resolution of an asylum seeker’s case, and it does not respond efficiently to large numbers in a short time span.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.029 | 0.022 |
| Scholarly communication | 0.014 | 0.007 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".