Refugee states critical refugee studies in Canada
Bibliographic record
Abstract
Exploring "refuge" and "refugee" as concepts that shape Canadian nation-building both within and beyond national borders, Refugee States takes an interdisciplinary and critical approach to describing how refugees articulate their relation to and defiance of official discourses. Through close examinations of refugee movements, contexts, and subjectivities, this collection reveals how Canada has relied upon the rejection and inclusion of refugees as a crucial means of statecraft. Bringing together renowned and emerging scholars from multiple disciplines, Nguyen and Phu illuminate the historical, political, and cultural conditions that produce refugees as well as the narrative of humanitarian benevolence that persists nationally and internationally. Highlighting landmark cases, the editors and contributors together develop critical refugee studies as a framework for understanding, nuancing, and critiquing the production of Canadian humanitarian exceptionalism – the international image and discourse of Canada as a liberal, tolerant, and welcoming haven for people fleeing oppression, persecution, and unfreedom. In doing so, Refugee States offers alternative modes of understanding past and present refugee passages to and within Canada, and brings to light the many ways in which refugee subjects navigate displacement, migration, and resettlement.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.055 | 0.022 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".