Bibliographic record
Abstract
During a time of uncertainty over collective identity and social transformation, Quebec novels started getting sick – after 1940, the number of narratives about illness, disease, and sick characters intensified. For the last seventy years, generations of authors have turned to medically oriented stories to represent day to day life and political turmoil. In Curative Illnesses, Julie Robert investigates how the theme of sickness is woven into literature and gauges its effect on depictions of Quebec’s national identity. Challenging the legitimacy of illness as a metaphor for the nation, Robert contests interpretations of illness-related literature that have presented Quebec itself as ailing. Through re-examinations of Quebec novels, Curative Illnesses shatters the illusion of congruency between the nation and the body, countering assumptions about nationwide weakness and victimization. For Quebec in particular, these assumptions have greater implications, because the separatist movement, policies of interculturalism, and majority language rights revolve around protecting and defending Québécois society and its cultural values. Robert skilfully demonstrates a more nuanced view of illness through a series of analyses focusing on works of literature from some of Quebec’s most renowned novelists, including Gabrielle Roy, André Langevin, Denis Lord, Hubert Aquin, Jacques Godbout, Pierre Billon, and Anne Bernard. Using an interdisciplinary approach that engages with nationalism, postcolonial studies, literature, rhetoric, and the medical humanities, Curative Illnesses explores how moving beyond earlier diagnoses offers new insights into nationhood.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.136 | 0.025 |
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".