« Acquérir un savoir sur le terrain plutôt qu’à l’école exclusivement ». Entretien avec Rachel Bouvet
Bibliographic record
Abstract
For Rachel Bouvet, literary studies are reinvented through contact with other disciplines: geography, for a geopoetic approach to texts, but also the life sciences, for a global approach to plants. More broadly, it is through movement, exploration and encounters with otherness that the researcher intends to bring literary research and creation into dialogue. Rachel Bouvet is a professor in the Department of Literary Studies at the Université du Québec à Montréal. She first worked on spaces and places in literature as part of a geopoetic approach, before turning her attention to the relationship between literature and botany. She co-founded La Traversée - Atelier de géopoétique, as well as GRIVE (Groupe de recherche interdisciplinaire sur le végétal et l'environnement). With Stéphanie Posthumus, she co-directed the volume Mouvantes et émouvantes. Les plantes à travers le récit (Presses universitaires de Montréal, 2024).
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.014 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.017 | 0.005 |
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".