The Impact of Canada–U.S. Safe Third Country Agreement on African Asylum Seekers in Canada
Bibliographic record
Abstract
AbstractAs the world becomes more globalized, migration is emerging as a major policy issue to contemporary governments. Thus, states have adopted immigration policies that extend beyond their jurisdiction, making the review of state actions a challenge. One such policy is the Canada–U.S. Safe Third Country Agreement (STCA). This policy has generated a range of social issues. However, no study has been conducted to understand the impact of the STCA on African asylum seekers in Canada. This qualitative study was based on the social construction and policy design theory. The central research question sought to understand the impact of the STCA on the right to life, liberty, and security of asylum seekers in Canada, while the subquestions were aimed at comprehending the meanings African asylum seekers in Canada ascribe to the asylum system and how they describe the impact of the Canada–U.S. STCA on their asylum-seeking experiences. Purposive sampling was used to recruit 22 research participants who met the inclusion criteria. Data were obtained through semistructured interviews and analyzed based on the seven steps used in analyzing responsive interviews. The findings showed that the STCA did not impact the rights to life, liberty, and security of asylum seekers. The results established the need for specific provisions of the STCA to be revised and that the asylum system and process are well organized but lengthy. The findings also revealed that the STCA impacted the asylum-seeking experiences of the participants and influenced their asylum-seeking decisions. The results could provide the basis for designing alternative policies to address the STCA’s loopholes by governments, nonstate actors, and the public to support planned positive social change related to people in need of protection.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.028 | 0.010 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.005 |
| 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".