Canadian citizenship in evolution: exploring six Canadian citizenship guidebooks from 1946-2012
Bibliographic record
Abstract
Six educational guidebooks on the rights and responsibilities of Canadian citizenship for new immigrants have existed for approximately six decades, arriving alongside the first Citizenship Act in 1947. These guidebooks have been circulated by the Canadian government in the hopes of educating immigrants unfamiliar with Canadian culture and democracy as adopted from Great Britain. By understanding democratic theory and its relationship to citizenship education, this paper explores four themes (how various governments have viewed the terms and conditions of becoming a citizen, the “vision” of Canada presented in the various guides, the rights and responsibilities of citizenship, and what the guidebooks imply about social inclusion and the integration of new Canadians) within each successive guidebook in order to analyse how different governments over the years have prepared newcomers for citizenship in Canada, and what constitutes successful integration. By exploring the various themes of each guidebook, this paper finds that government-sponsored citizenship guidebooks are products of both domestic and international socio-political atmospheres, whose goal is to present to newcomers citizenship education, as well as a vision of Canada that reflects partisan attitudes toward various public policies.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.023 | 0.007 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 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".