Borders and in-betweenness : translating and understanding the “lines” in three collections of short stories written by Alice Munro
Bibliographic record
Abstract
L’œuvre de la nouvelliste canadienne Alice Munro, striée de lignes, est parcourue de multiples tensions. Dans cette thèse, je propose de traduire trois de ses recueils (Lives of Girls and Women [1971], Something I’ve Been Meaning to Tell You [1974] et Who Do You Think You Are? [1978]) et d’étudier ce passage vers le français au prisme de la ligne, qui s’inscrit ici dans une troisième voie possible, entre traductions sourcière et cibliste. Il s’agit de retranscrire ces textes tout en suggestions et non-dits, sans dénaturer l’univers de l’autrice par un trop-plein d’explicitations, et de trouver un équilibre entre la facilité à comprendre pour le lecteur d’une part et la fidélité à l’esprit de l’œuvre, d’autre part. La traduction requérant un regard au plus près du texte, ce travail s’accompagne d’une analyse littéraire de ces ouvrages. Cette étude s’articule autour de quatre axes : les lignes prennent tour à tour les formes de frontières délimitant l’espace diégétique, d’une séparation entre hommes et femmes issue d’un modèle patriarcal, de divisions sociétales plus larges, et d’une limite floue entre fiction et réalité. Cette thèse vise ainsi à interroger ce qui se trouve de part et d’autre de ces lignes, mais surtout à ce qui se développe dans cet entre-deux.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.025 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".