The Institutional Arrangements and Resilience of Québec Local Communities in the Welcoming and Integration of Immigrants: A Theoretical and Practical Contribution
Bibliographic record
Abstract
This doctoral thesis focuses on the role of cities in immigration, particularly in Québec.The literature shows that cities can intervene, and are progressively doing so, in order to ensure a complete offer of services to newcomers, in particular in the coordination of local actors.Thus, this research aims to answer the following question: How do local communities in mid-sized Québec cities welcome and integrate immigrants?This research seeks to understand the capacity of local communities to mobilize stakeholders, coordinate services dedicated to immigrants and deliver them.The research builds on the lessons learned across the rest of Canada.Two case studies are conducted, in Gatineau and Québec City.The analysis is based on multilevel governance theoretical framework, where immigration is a responsibility increasingly shared between various orders of government.This present study leads to empirical and theoretical contributions.At the empirical level, the two case studies make it possible to trace the contours of the Québec model of governance in terms of immigration.They show that the communities have taken responsibility for themselves and that the cities have assumed leadership to ensure the coordination of local actors and to meet the needs of newcomers, although the institutional arrangements remain sub-optimal.The theoretical contributions of this thesis are twofold.First, the case studies conducted in this thesis refines an analysis grid developed by other authors.Two elements of analysis are added, analyzing the engagement of the political side versus the administrative side, as well as the sufficiency of financial resources.These two elements of analysis have the potential to enrich the understanding of the portrait as well as the evaluation of institutional arrangements.Second, the other theoretical contribution is the development and definition of the concept of 'governance void'.Governance void is defined as an absence of clearly stated policies on the sharing of responsibilities between orders of government and other stakeholders.This absence of policy gives way to all types of structures, often suboptimal, that vary depending on regions and through time.In a context of multilevel governance, the roles and responsibilities of the actors must be clearly defined and understood.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.017 | 0.011 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".