Bibliographic record
Abstract
L’oeuvre d’Edgar Allan Poe a exercé une influence profonde sur celle d’Anne Hébert. Cette dernière a été, dans sa jeunesse, une lectrice assidue des oeuvres de l’écrivain américain, à l’instar de plusieurs écrivains canadiens-français qui l’ont précédée, notamment Octave Crémazie, Émile Nelligan et Hector de Saint-Denys Garneau. Cet article tente d’explorer cette dimension importante de l’américanité de l’oeuvre d’Anne Hébert en mettant en lumière quelques unes des ressemblances entre cette oeuvre et celle d’Edgar Allan Poe : le recours au fantastique, l’esthétique gothique, le rôle dévolu au fait divers, l’imaginaire de la fin, la réflexion sur la poésie, etc. L’étude de ces ressemblances permet de jeter un éclairage nouveau sur certains aspects essentiels de l’oeuvre d’Anne Hébert, en les situant justement dans le contexte nord-américain de leur genèse.
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 | 0.001 | 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 | 0.018 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 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".