Comparing Ambiguities: Municipalities, Francophone Minority Communities and Immigration in Canada
Bibliographic record
Abstract
Abstract This article analyzes the implication of municipal governments and civil society actors in immigration through multilevel and collaborative governance arrangements. It argues that studying the roles of ambiguities is critical to understanding the activism of political entities with ill-defined status and mandates, such as municipalities and francophone minority communities (FMCs). This research adds to the literature on the “local turn” by highlighting that ambiguities are both a condition—that is, a driver that makes collaborative and multilevel arrangements work—and an outcome of collaboration practices, characterized by ambiguities regarding the balance of power, the aims of collaboration in a competitive sector and conflicting forms of accountabilities. The article identifies three approaches that actors use to deal with these ambiguities in a context where resources are not equitably distributed and where the role of the federal government is critical. In this configuration, municipalities and FMCs develop adaptive, rather than transformative, approaches to ambiguities.
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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 | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.021 | 0.012 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".