Pragmatism, Ethics and Aesthetics in the Narratives of the Japanese-Canadian Displacement
Bibliographic record
Abstract
Pragmatic, ethical and aesthetic purposes are simultaneously combined in the narratives depicting the decreed mass removal of Japanese Canadians from their Pacific Coast homes during World War II. When dealing with this extremely painful travel experience, Canadian writers of Japanese ancestry have adopted a pragmatist approach that stresses—rather than contradicts—reciprocally reinforcing ethical and aesthetic values. By emphasizing the elements of beauty, pleasure and harmony that are essential in any artistic creation, such authors have both enhanced moral reflection on the part of their audience and strengthened the practical efficacy of their factually grounded works of fiction. All these writers are keen on providing accurate representations of a traumatic journey they were involved in, either directly or through the memoirs of the members of their families who were forced to undertake it. In their writings there are recurrent descriptions of evacuees standing on railway platforms while being insulted and threatened by vociferous crowds. These migrants generally remain silent after boarding CPR trains with their remaining possessions crammed into the single suitcase that each person is allowed to carry as luggage on the trip eastwards. But as Japanese-Canadian novelists have narrated the same events from various perspectives and focused on different aspects of their ordeal, their accounts are far from being uniform. Their literary texts are marked by the categories of genre, gender, and ethnicity, as well as by the personal attitudes of each individual author. The characters portrayed express a wide range of feelings: hope, patience, calmness, serenity, resignation, fear, shame, distress, bitterness, and anger. They invariably miss the ocean, which they mentally connect with their past freedom, and some of them manage to soothe their emotional wounds when the landscape of the prairies brings them memories of their beloved sea. Some of these displaced people find comfort in the magnificent scenery that is ironically set up as the physical background to the hardships suffered. Unable to move on unrestrained once they have reached their destination in the internment camps or in the ghost towns where they have been relocated, others resort to fantasy in order to escape through imaginary voyages that release them from their otherwise unbearable situation.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.053 | 0.054 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".