The Multilevel Governance of Immigration and Settlement: Making Deep Federalism Work
Bibliographic record
Abstract
Abstract. This study addresses the question of how best to ensure that national immigration policies are appropriately adjusted to meet the disparate requirements of different communities. We argue that this is the core objective of multilevel governance, which, however, has become freighted with competing ideological objectives, objectives that are perhaps best expressed in Hooghe and Marks's distinction between type I and type II governance, the former oriented to collective decision making and the latter embodying market-oriented approaches to governance. Our argument is that these competing sets of ideologically driven objectives divert multilevel governance away from its core objective of appropriateness to community circumstances. An accompanying article (Leo and Enns, 2009) explores problems posed by ideologically driven, type II multilevel governance in Vancouver. The current article takes up a contrasting case, that of the Canada-Manitoba Agreement on Immigration and Settlement, focusing especially on Winnipeg. We find that in this case the provincial government chose an approach to multilevel governance that did not hew to either type I or type II governance templates, but drew on both to build an impressively successful system of immigration and settlement, carefully tailored to meet the requirements of disparate Manitoba communities. Success was built not on the application of a preconceived template for good governance but on resourcefulness and flexibility in working out ways of making national policies fit local circumstances. Résumé. La question que pose cette étude est la suivante : comment s'assurer que les politiques nationales concernant l'immigration et l'insertion sociale correspondent parfaitement aux besoins disparates des communautés différentes? Nous prétendons que c'est précisément la raison d'être de la gouvernance multipalier. Or, celle-ci est présentement surchargée de préoccupations idéologiques opposées et contradictoires qui trouvent leur meilleure expression dans la distinction que Hooghe et Marks ont faite entre le type I et le type II de gouvernance; l'un s'oriente vers la méthode collective de décision, l'autre incarne les approches de la gouvernance déterminées par les contraintes du marché. L'essentiel de notre argument est que ces approches idéologiques opposées entravent et contredisent l'objectif principal de la gouvernance multipalier, qui est de rendre les politiques gouvernementales sensibles aux circonstances particulières des communautés. Un article connexe (Leo et Enns, 2009) aborde les difficultés que pose, à Vancouver, la gouvernance multipalier de type II déterminée par des contraintes idéologiques. Le présent article aborde un cas tout à fait contraire, soit celui de l'Entente Canada-Manitoba sur l'immigration et l'insertion, centré sur Winnipeg. Nous constatons que, dans ce cas, le gouvernement provincial a opté pour une approche de la gouvernance multipalier qui ne cadrait pas avec les modèles de gouvernance de type I ou II, mais qui s'est inspirée des deux pour bâtir un modèle d'immigration et d'insertion qui est d'autant plus impressionnant et bien réussi qu'il est méthodiquement conçu en fonction des besoins disparates des communautés manitobaines. Ce succès provient non pas de l'application d'un modèle préconçu de bonne gouvernance, mais d'une quête ingénieuse et flexible des moyens qui permettent de concilier les politiques nationales et les circonstances régionales.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.022 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".