THE DEPICTION OF QUEBEC SOCIETY THROUGH THE NOVELS OF GÉRARD BESSETTE AND MARIE CLAIRE BLAIS
Bibliographic record
Abstract
The study investigates the portrayal of Quebec society during the transition from the Great Darkness to the Quiet Revolution through the analysis of two novels, “Le Libraire” by Gérard Bessette and “Une saison dans la vie d’Emmanuel” by Marie Claire Blais. The objective is to analyze the presence and effects of these two significant movements in Quebec francophone literature. The research addresses questions such as whether the socio-political changes of the 60s influenced the literature of that era, the reflection of the Great Darkness and the Quiet Revolution in the selected novels, and how the main characters and stories represent these themes in contemporary society. This study employs a qualitative methodology, relying on secondary data from various sources. The historical method is used to critically investigate past events to produce accurate descriptions and interpretations, while the analytical method helps define research needs and problems and establish a strategy for obtaining answers. The results reveal that “Le Libraire,” captures the transitional phase by depicting the lingering conservatism of the Great Darkness alongside emerging new values. “Une saison dans la vie d’Emmanuel” vividly portrays the suffering and societal injustices of the Great Darkness era. These novels illustrate the social, economic, political, and cultural shifts in Quebec society during this transformative period. The findings suggest that these novels not only document historical realities but also highlight the ideological foundations and social challenges that shaped modern Quebec. By analysing the themes and narratives in both works, the study underscores the critical role of literature in reflecting and influencing societal change.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.027 | 0.015 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 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".