La berceuse au-delà de toutes les frontières : l’exemple du roman Ru de Kim Thúy
Bibliographic record
Abstract
Dans cet article, nous examinerons les manières dont l’écrivaine Kim Thúy joue avec les codes de la berceuse pour assurer la transmission de l’histoire individuelle et collective relative à la narratrice dans son premier roman, Ru (2009). Notre étude sera effectuée en deux temps : nous analyserons d’abord les éléments sémantiques et poétiques (répétition, récurrence, rythme, division du texte) utilisés dans le récit et nous nous pencherons ensuite les éléments thématiques explicitement liés à la berceuse dans ce roman, notamment le désir de transmission, l’enfance, la maternité et la collectivité. En nous basant sur les théories des écritures migrantes et mémorielles, de l’hybridité et de la filiation, nous montrerons que Kim Thúy parvient habilement à brouiller les frontières entre le roman mémoriel et la berceuse. Enfin, nous espérons que notre étude contribuera à mieux saisir et à (re)définir ce qu’est une berceuse, et à montrer la fluidité, la beauté et la puissance de ce genre.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.009 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".