Bibliographic record
Abstract
Migrants continue to seek refuge in the United States despite harsh deterrence policies. The failure of even the most punitive exclusionary tactics points to the need for new immigration strategies. Rather than constructing additional ineffective and inhumane barriers, an alternative strategy should focus on building the scaffolding for successful immigration. This Article explores one way of supporting successful immigration: practices encouraging newcomers to cultivate an identity of civic belonging. To do so, it identifies and analyzes implied messages about civic participation conveyed to refugees prior to being resettled in Canada and the United States. When a refugee is accepted for permanent resettlement to a new country, the receiving government’s first meaningful opportunity to welcome and impart a sense of civic belonging occurs during a pre-departure orientation program. The present study examines how law is framed during the pre-departure orientation programs offered by Canada and the United States, providing insight into a newcomer’s official introduction to conceptions of citizenship, rights, and obligations. The research is based largely on a qualitative analysis of the orientation textbooks conducted within a critical legal theory framework, and is informed by fieldwork in Amman, Jordan. This Article reveals that Canada’s approach to law signals that resettled refugees are new participants in a polity in which members have rights and obligations to one another. By contrast, the U.S. treatment of law implies that refugees are outsiders and suspected of harboring criminal tendencies. Legal scholars and sociologists posit that government policy towards newcomers influences their civic incorporation. Consequently, by offering orientation materials that infer that refugees are potential offenders, the United States could well be impairing the future civic belonging and integration of these newcomers.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.013 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.008 |
| 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".