“Landscape–of–the–Heart”: Transgenerational Memory and Relationality in <i>Roy Kiyooka's Mothertalk: Life Stories of</i> Mary Kiyoshi Kiyooka
Bibliographic record
Abstract
“HOW ELSE WILL THEY KNOW there is a landscape etched on their hearts which got sown in a bamboo grove?” asks Mary Kiyooka, autobiographical narrator of Nisei artist and poet Roy Kiyooka's auto/biography Mothertalk: Life Stories of Mary Kiyoshi Kiyooka (Kiyooka 1997a, 160). How else but by frequently going “back” to the place of parental origin, that is, to Japan, or, more specifically, to Tosa Province on the island of Shikoku? “Place” is crucial in Kiyooka's narrative, both for the autobiographical narrator and for her descendants; Mothertalk presents an exploration of an individual as well as a family past shaped by an intense awareness of the multilayered—emotional, cultural, historical—inscriptions of both locationality and translocal processes. This exploration, as will be argued below, is auto/biographical rather than autobiographical or biographical. In this exceptional text, to put it with Adriana Cavarero's phrasing in a different context, “autobiographical and biographical genres are superimposed upon one another” (2006, pos. 2910): the story of the mother told as a relational story of her remembrance of her “real home” (Kiyooka 1997a, 29) and her son's exploration of “Japan” as a touchstone for his own subjectivity. Mothertalk , as the first-person narrative of an immigrant woman, has been mainly read with a focus on its Canadian subject matter, not least because of the significant editorial interventions by her son Roy and by the editor Daphne Marlatt. Marlatt, according to Susanna Egan and Gabriele Helms, “felt strongly that Mary's stories were important for Canadian history…. Ultimately, [Marlatt's] choices have determined that Mary's life stories find their place in the English reader's understanding of the Japanese Canadian experience” (Egan and Helms 1999, 62). Also, the inclusion of two additional essays by Roy Kiyooka in the book, both of which deal with Japanese Canadian history and subject formation, directs the reader's attention to Mothertalk as a narrative centrally embedded in a Canadian context. While the text certainly contributes significantly to an understanding of the complexities of the lives of Japanese immigrant women in Canada, the multilayered structure of the book and its genesis, documented impressively by Susanna Egan and Gabriele Helms as well as by Joanne Saul, also suggest a more strongly pronounced transnational focus.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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 teacher head, 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".