The Reality beneath the Rhetoric: Probing the Discourses Surrounding the Safe Third Country Agreement
Bibliographic record
Abstract
RESUMtApr~s les attaques terroristes du 11 septembre 2001, le gouvernement canadien a poursuivi les n6gociations avec les Etats-Unis au sujet de l'Entente concernant les tierspays stirs.Cette entente, qui interdit la participation au syst6me de d6termination du statut de r6fugi6 aux rdfugids qui ont voyag6 dans un pays rdput6 s6curitaire, a W prise en considdration au Canada depuis la fin des ann6es 1980.Bien que les tentatives de donner aux Etats-Unis le titre de pays sfir aient dchou6 depuis le 11 septembre 2001, le Canada a repris ses efforts et les Etats-Unis ont manifest6 en retour leur intention de discuter.Le moment particulier de cette initiative a conduit I'auteure du prdsent article A se demander quel impact les attaques terroristes aux 1ttats-Unis ont eu sur l'61aboration de la politique canadienne relative aux rdfugi6s.* Lara Sarbit, B.A. (Hons.)(British Columbia), M.A. (Toronto), is currently completing her LL.B. at Osgoode Hall Law School.She would like to thank Janet Mosher, the Immigration Division at Parkdale Community Legal Services, Stephen Caplan, and her family for their assistance
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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 | 0.045 | 0.076 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.030 | 0.085 |
| Scholarly communication | 0.031 | 0.022 |
| Open science | 0.004 | 0.014 |
| Research integrity | 0.021 | 0.032 |
| 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".