Memories of Internment: Narrating Japanese Canadian Women's Life Stories
Bibliographic record
Abstract
This paper attempts to bridge the dichotomy of "historical truth" and personal recollection by exploring the sociological concept of memory. Drawing on 30 oral testimonies of Nisei (second generation) Japanese Canadian women, I explore the diverse and often complex ways in which Nisei women remember the internment, with particular attention to the intermingling of past and present, the relationship between teller and listener, as well as the layering of personal and public narratives, in the construction of these memories. The theme of silence and telling is also explored, with the understanding that the literacization of memories is always a political act. Cet article essaie de relier la dichotomie de la « vérité historique » et des souvenirs personnels en explorant le concept sociologique de la mémoire. M'inspirant de 30 témoignages oraux de femmes canadiennes japonaises Nisei (deuxième génération), j'explore les manières variées et souvent complexes dont les femmes Nisei se souviennent de l'internement, en accordant une attention toute spéciale au mélange entre le passé et le présent, à la relation entre le narrateur et l'auditeur et à la superposition de narrations personnelles et publiques dans la reconstruction de ces souvenirs. Le thème du silence et de la narration y est aussi exploré en sachant que toute transposition par écrit de souvenirs représente toujours un acte politique.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.018 | 0.009 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".