Histoires de pionniers français dans l’Ouest canadien: Le cas d’Un Héros Malgré Lui de Marcel Durieux (Western Canadian French Pioneer Stories: The Case of Marcel Durieux’s Un Héros Malgré Lui)
Bibliographic record
Abstract
French Abstract: Traditionnellement delaisses par les litteraires, les recits pionniers se trouvent generalement rapportes au genre du journal ou de la chronique. C’est notamment le cas d’Un heros malgre lui de Marcel Durieux dont les prefaciers, Roger Motut et Maurice Legris, louent le style a la fois simple et concret. A contre-courant de cette lecture, nous montrerons que le texte de Marcel Durieux est travaille par une ambition romanesque qui se manifeste a la fois par la construction d’une temporalite complexe, le desir de restituer la diversite culturelle et linguistique de la societe pionniere et enfin le recours frequent aux metalepses. En somme, il s’avere pertinent de considerer ce type de recits comme des textes romanesques susceptibles d’enrichir le patrimoine litteraire de la francophonie de l’Ouest.English Abstract: Pioneer stories have traditionally been ignored by literary critics and associated with literary genres such as chronicles and diaries. This is the case of Marcel Durieux’s Un Heros Malgre Lui, whose style has been praised by the prefacers Roger Motut and Maurice Legris for being both plain and concrete. This article will take a different view and demonstrate that Marcel Durieux’s text aspires to be a fictional narrative insofar as it builds a complex time-span, restores the cultural and linguistic diversity of pioneer society and frequently turns to metalepsis. Considering this type of narrative as fiction will likely enrich Western Canadian francophone literary heritage.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.024 | 0.012 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".