« Le désert progresse » : mirages postmodernes de l’Ouest américain dans les fictions françaises et québécoises
Bibliographic record
Abstract
This dissertation examines the representation of the American desert in contemporary French and Québécois fiction, where it is often portrayed as an expanding, destabilizing force that overwhelms the narrative space. It investigates how Francophone authors engage with this landscape through a postmodern lens that reflects anxieties about American cultural and geopolitical dominance, while also exploring the desert as a space for narrative experimentation. The analysis engages with how the notion of desertification shifts from its colonial connotations – tied to France’s civilizing mission in the Sahara – to a broader metaphor for environmental collapse and civilizational decline. Drawing on narratological, comparative, and ecocritical methodologies, this study identifies recurring textual strategies, including narrative embedding, the aesthetics of the abyss, and the destabilization of linear temporality. It situates the desert as a narrative and geographic interstice, where Hollywood influence, colonial legacies, and European sensibilities intersect to form a network of aesthetic and ideological tensions. The findings reveal that Francophone fiction moves beyond a simple rivalry with U.S. cultural production, shifting from initial postmodern estrangement to a more autonomous reappropriation of the desert, especially in the Québécois context, where decolonial and ecological concerns reshape the desert imaginary.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.014 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".