Intergenerational Storytelling and Transhistorical Trauma: Old Women in Contemporary Canadian Fiction
Bibliographic record
Abstract
Intergenerational Storytelling and Transhistorical Trauma: Old Women in Contemporary Canadian Fiction examines fictional representations of intergenerational storytelling exchanges between old diasporic women and younger characters. Focusing on three Japanese Canadian novels and two Trinidadian Canadian novels, written post-1970s, I examine the intergenerational tensions between telling personal and collective traumas of the past and maintaining silences within the family. Hiromi Goto’s Chorus of Mushrooms, Joy Kogawa’s Obasan, Darcy Tamayose’s Odori, Shani Mootoo’s Cereus Blooms at Night, and David Chariandy’s Soucouyant provide multiple generational and cultural optics through which to address how the past continues to reside within and inform the present moment, and thus impact one’s subjectivity and sense of belonging or dislocation. These novels characterize old racialized women in Canada as complex figures who disrupt assumptions about memory and madness, and their storytelling engagements highlight the impact of difference, of temporality, and of intergenerational transmissions. This study analyzes different narrative structures and strategies that emulate the symptoms of traumatic “belatedness” and provide readers with an understanding of “reciprocal storytelling” as a means of “bearing witness” to personal and transhistorical trauma. Drawing together work in literary trauma studies with narrative theory, I investigate the challenges and implications of articulating different types of trauma within the literary genre of the novel, and I argue these old women’s stories contribute important age and cultural perspectives to theories in social and critical aging and trauma studies.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.029 | 0.014 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".