Policy-making for immigration and integration in Québec: degenerative politics or business as usual?
Bibliographic record
Abstract
Policy Design Theory (PDT) predicts that the distribution of the costs and benefits of governmental intervention depends on the social construction and level of power of target groups. The case of Québec, Canada, which recently went through acrimonious policy debates on immigration and integration issues, does not correspond to this pattern. Degenerative politics – that is, the stigmatization of powerless groups and an unequal distribution of the costs and benefits of governmental intervention to the detriment of the most vulnerable – did not occur even if the conditions were seemingly in place to produce it. Using Québec as a ‘most likely’ case, I show that the policy-making sphere remained immune to the degenerative dynamics that took hold in the media and the legislature. More precisely, I argue that three interrelated factors explain the results: past policies and their unintended consequences, an implementation structure committed to the needs of immigrants, and the specific incentive structure facing political actors. The results question the transferability of PDT outside of the institutional setting of the USA, where it was first developed and applied.
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.009 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".