Bibliographic record
Abstract
Depuis 2016, le Canada fait face à un afflux de demandeurs d’asile qui traversent la frontière Canada/États-Unis entre les points d’entrée officiel. Ce phénomène est largement documenté dans la presse nationale et internationale pour présenter le pays comme une « terre s’asile ». Toutefois, si ces flux migratoires s’insèrent dans une tradition de refuge de la part du Canada, ils inquiètent aussi une partie de l’opinion politique qui voit en eux le signe d’une « crise migratoire » que le Canada peine à résoudre. Cet article reviendra sur l’image traditionnelle du Canada afin d’analyser ensuite les statistiques concernant l’arrivée de réfugiés pour présenter la combinaison de facteurs qui expliquent ce phénomène et notamment le rôle joué par l’élection de Donald Trump à la présidence américaine.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.027 | 0.018 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 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".