Bibliographic record
Abstract
Canada’s security policies have had an impact on refugee protection. Canadian judges use international law principles in refugee issues, and ensure constitutional human rights protection to “everyone”, including refugees and asylum-seekers. Canada has expanded the refugee definition to persons at threat of torture, according to the United Nations Convention against Torture. But, on recent security issues, Canada has had difficulty to reconcile international law and domestic law, in terms of human rights guarantees. Return to torture has been technically rendered possible by the Supreme Court of Canada, as a matter of constitutional interpretation. One particular mechanism, the “security certificate”, has been intensely scrutinised by courts and found wanting in many cases. The secrecy surrounding the information on which the certificate is based has been criticised, as have been the ex parte proceedings, the indefiniteness of the detention, the limitations on the role of the “special advocate”, and so forth. Judges have felt increasingly irritated by the intrusion of security intelligence in judicial proceedings. Canada is (now more than before) reluctant to submit to international human rights scrutiny on migration and security issues, arguing that it relates to territorial sovereignty.
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 | 0.008 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.030 | 0.008 |
| Scholarly communication | 0.018 | 0.003 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 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".