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Record W7135335252

« Le désert progresse » : mirages postmodernes de l’Ouest américain dans les fictions françaises et québécoises

2025· other· en· W7135335252 on OpenAlexaboutno aff
Marie Bellec

Bibliographic record

VenueScholarly Commons (University of Pennsylvania) · 2025
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsDesert (philosophy)NarrativePostmodernismHollywoodFrenchEcocriticismIdeologyColonialismRepresentation (politics)
DOInot available

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.426
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0000.002
Open science0.0030.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.015
GPT teacher head0.242
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueScholarly Commons (University of Pennsylvania)French-language works237,207