Seeking safe haven in Canada: geopolitics and border crossings after the Safe Third Country Agreement
Bibliographic record
Abstract
This chapter examines border-crossings as a strategy of human security between Canada and the United States to understand the fraught role of Canada in relation to its powerful neighbour. The 2004 Safe Third Country Agreement prevents most asylum seekers from crossing the land border at designated ports of entry between the two countries. In 2017, President Trump enacted an entry ban on specific nationalities and increased enforcement against undocumented migrants. Asylum seekers from the US began walking across the border to Canada at non-designated ports of entry. While Canada has not generally accepted refugees who are US citizens, people fleeing military conscription during the Vietnam War were accepted. More recently, soldiers refusing to serve in the US occupation of Iraq have made refugee claims, albeit with less success. The chapter illustrates how Canada and the US restrict access to asylum, forcing people to forge their own forms of human security.
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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 | 0.002 | 0.006 |
| Science and technology studies | 0.035 | 0.010 |
| Scholarly communication | 0.013 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.017 | 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".