Dôre Michelut: Voicing One’s Linguistic and Existential Hybridity Through Multilingual Writing and Self-Translating
Bibliographic record
Abstract
This article investigates the practice of self-translation in the context of migration by examining the literary production of Dôre Michelut, a Canadian author of Italian origins. It specifically illustrates how Michelut’s writing and translating are rooted in her migrant experience and operate as instruments through which the author can voice her hybrid identity and bridge Italian and Canadian worlds. Michelut’s experience of living in-between multiple linguistic and cultural spaces is recreated on the written page, which becomes the site where these multiple spaces are connected and interwoven. The act of writing and translating are thus interrelated in a continuous process of creation that leads to the production of a “hybrid text” and to the enactment of a “hybrid process.” In the first case, hybridity emerges through multilingual writing. In the second case, it is articulated around a specific form of self-translation that is in-between writing and translating.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.036 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| 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".