Ãtude génétique de "Jeannot-la-Corneille" de Gabrielle Roy
Bibliographic record
Abstract
Researchers currently are according a great deal of importance to the genetic analysis of Gabrielle Roy's writings. Indeed, the author's manuscripts reveal important details about her creative process. In this thesis, we study the changes the author made to both style and content at different stages of the writing of "Jeannot-la-Corneille", one of the recits making up Cet ete qui chantait. The latter is one of Roy's least studied books. Our analysis of the modifications the author made to the content and style of her texts allows us to understand the reasons behind these changes and gives us as well a sense of Gabrielle Roy's creative work. Admired for the apparent ease with which she writes, the author reworks her text tirelessly in order to achieve the desired effects: precision, accuracy and musicality. Adjectives, adverbs, nouns, all parts of speech are subject to change in this quest to improve descriptions and, in so doing, deliver more effectively a message of hope.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.027 | 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".