Bibliographic record
Abstract
Bien que Laure Conan occupe une place majeure dans l’histoire littéraire du xix e siècle québécois, il existe un décalage entre la mémoire de cette écrivaine et sa vie réelle. C’est cet écart que l’article mesure, en proposant également quelques hypothèses sur ses fondements et ses causes. Les auteurs s’intéressent d’abord aux représentations fictives de Conan dans la littérature de manière à cerner l’imaginaire entourant l’écrivaine. Ce portrait est ensuite confronté aux données factuelles concernant la trajectoire et la production de l’écrivaine, ce qui met en lumière une tout autre image de Conan, qui est loin de se réduire à celle largement répandue de pionnière sacrifiée. Ce parcours montre également l’importance d’un pan occulté de sa production littéraire, celui du roman historique, auquel seuls quelques commentateurs se sont intéressés.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.019 | 0.017 |
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; both teacher heads agree on what is shown here.
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".