Bibliographic record
Abstract
Cet article porte sur la ruine du vivre-ensemble dans trois romans québécois qui déjouent les conventions du réalisme littéraire. Oscar De Profundis de Catherine Mavrikakis (2016), Le poids de la neige de Christian Guay-Poliquin (2016) et Tu aimeras ce que tu as tué de Kevin Lambert (2017) ancrent leurs personnages dans des lieux ruinés et mortifères où le vivre-ensemble emprunte une forme spectrale relevant d’une mythologie d’un autre temps. Les gueux du Montréal postapocalyptique de Mavrikakis et les habitants du village enneigé de Guay-Poliquin, s’ils se rassemblent et unissent temporairement leurs forces, le font sous l’influence de jeux d’alliances opportunistes, voués non pas à la défense d’un projet social, mais bien à la survie de quelques individus triés sur le volet. Dans le roman de Kevin Lambert, les lieux urbains sont transfigurés, transformés en pièges parfois mortels, coupables d’infanticides qui illustrent de manière radicale la ruine des solidarités communautaires. Je m’attacherai en somme à la manière dont les lieux romanesques font signe vers les ruines d’un certain idéal, voire d’un fantasme politique, « marqué lui-même par un certain usage du temps, l’usage de la promesse » (Rancière, Aux bords du politique, p. 23).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.011 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 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".