Rencontre avec Andréane Frenette-Vallières : Écriture, Territoire et Identité
Bibliographic record
Abstract
Dans cet entretien mené par Christophe Premat au Centre d’études canadiennes de Stockholm, Andréane Frenette-Vallières évoque son lien intime avec le territoire québécois, particulièrement Natashquan, un lieu qui nourrit son écriture par son immensité et sa rudesse. Son œuvre est marquée par une exploration introspective où le territoire joue un rôle central. Dans Juillet, le Nord (2025), elle décrit une quête identitaire à travers la découverte d’un paysage forestier et marin. Sestrales (2020) interroge la sororité et l’identité féminine dans une relation ambiguë entre deux femmes vivant en ermite. Son dernier livre, Tu choisiras les montagnes (2022), se construit en fragments poétiques qui explorent la violence de genre, la solitude et l’identité. Inspirée par Clarice Lispector, Andréane Frenette-Vallières développe une polyphonie narrative où le silence, les vides et les brisures de la pensée sont des formes d’expression essentielles. Elle souligne aussi la vitalité actuelle de la poésie au Québec, notamment chez les jeunes, comme un espace de liberté, de guérison et de questionnement identitaire. Abstract This interview was transcribed from the conversation given by Andréane Frenette-Vallières during her visit to the University on May 30, 2024. The interview was published on https://www.youtube.com/watch?v=Tm-yS8sc0Ro. We would like to thank the International Association of Quebec Studies for funding the publication of this interview. The author thanks Éditions du Noroît and Françoise Sule for their logistical support. Keywords: Territory; Poetry; Identity; Gender violence; Narrative polyphony
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.012 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".