Strengthening Canadian citizenship: but how and for whose benefit? The rise and fall of (Bill) C24, or towards a hierarchized Canadian citizenship
Bibliographic record
Abstract
While Statistics Canada evidences immigration to be a key driver of Canada’s population growth, unwelcoming immigration settlement policies and Canadian citizenship legislation combine to impede recent immigrants’ integration. Above all, citizenship policy plays a pivotal role in easing newcomers’ integration into the host polity by transforming them into citizens. Through naturalization, immigrants acquire legal citizenship; their substantive citizenship makes them enjoy rights and exercise responsibilities embedded in, and defined by citizenship policy. This paper argues that, by institutionalizing a conditional citizenship for new immigrants, recent changes to the Canadian citizenship regime brought by C-24 in June 2014 then repealed by C-6 in June 2017, not only weaken but jeopardize both legal and substantive citizenship of dual Canadian citizens and, consequently, hinder their successful integration into the Canadian polity. This study concludes that the lived experiences of recent immigrants mark a distinction between new Canadians’/visible minorities’ alientity and mainstream Canadian identity.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.027 | 0.015 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".