Playing with lives under the guise of fair play: the safe country of origin policy in the EU and Canada
Bibliographic record
Abstract
The safe country of origin (SCO) policy has been implemented by the European Union (EU) and Canada as a way to deal with a backlog of asylum applications, increase efficiency, reduce administrative costs and exclude fraudulent refugee claims. The concept is founded on the assumption that a democratic country with an adequate human rights record is safe for individuals because there is generally no risk of persecution. While this attempt at creating more efficient asylum procedures may seem sensible in theory, an in-depth analysis will reveal that the practice is a prejudicial, exclusionary, and dangerous development that could potentially deny asylum to those who are in genuine need of international protection. Contributing to the existing body of literature, our paper provides a comparative analysis of how SCO is rationalised in Canada and the EU. We argue that the policy is a political response to unwanted migration and a migration management tool used to deter and limit asylum applications from what States deem as 'bogus' refugees, while facilitating the removal of these individuals. Whether these goals have been attained remains debatable. However, as currently applied, the SCO policy is detrimental to the human rights of asylum seekers.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.025 | 0.014 |
| Scholarly communication | 0.011 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".