The Stories They Carried: Reflections of Vietnamese-Canadians 40 Years after That War
Bibliographic record
Abstract
This article explores the narratives of former refugees from Vietnam who resettled in Canada. Each of these stories highlights the profound dilemmas, motivations, and experiences of Vietnamese refugees. Collectively, they demonstrate the remarkable resilience of this community, and their determination to survive and remake themselves in Canada. The discussion illuminates the diversity and complexity of my respondents’ senses of belonging, homes, and homelands, and how such notions and ties are continually evolving. The research aims to contribute to the postwar/refugee discourse, and to move the field beyond the parameter of the war and exodus from Vietnam, in order to study Vietnamese in all their complexities—in a new locale.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.061 | 0.028 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.005 | 0.012 |
| Insufficient payload (model declined to judge) | 0.006 | 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".