Gestion de lâimmigration et politiques dâintégration dans des Etats fédéraux : Belgique et Canada
Bibliographic record
Abstract
La Belgique et le Canada sont deux Etats qui expérimentent un fédéralisme (1) dans un cadre multinational (4) et qui ont développé des réponses distinctes aux tensions engendrées par la diversité culturelle et linguistique. Aujourdâhui, ces pays se trouvent également confrontés à la gestion de la diversité induite par lâimmigration et doivent opérer des choix importants en ce qui concerne la sélection (2) mais aussi lâintégration des nouveaux arrivants (3). Dans cette optique, cette contribution a pour ambition de comparer ces deux fédérations en ce qui concerne leur gestion de lâimmigration et leurs politiques dâintégration des nouveaux arrivants, en particulier dâun point de vue institutionnel et juridique. Quels sont les mécanismes mis en place ? En quoi se distinguent-ils ? Quelles sont les leçons à tirer de chacun des cas ?
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.016 | 0.007 |
| Scholarly communication | 0.008 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".