Canadians in Trouble Abroad: Citizenship, Personal Security, and North American Regionalization
Bibliographic record
Abstract
This article concerns itself with what happens to the universal/particular character of citizenship in the context of North American regionalization. It takes as a starting point several incidents where Canadian citizens have called on their government to help them through crisis situations abroad, and then taken it to task for not helping enough. The cases analysed involve Canadian tourists in Mexico who died violently and whose families have used the media to pressure the Canadian government to obtain justice from Mexico. Mass calls for help following natural disasters and war, and the case of Maher Arar, a Canadian citizen “rendered” by the United States to Syria where he was tortured, are also considered to conceptualize “citizens in trouble abroad” claims. The article finds that such claims reinforce a Canadian sense of citizenship where political identity remains rooted firmly with(in) the nation‐state, despite the country's engagement in a deep regionalization project. Maher Arar is a Canadian citizen. 1
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.026 | 0.015 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".