Bibliographic record
Abstract
The representation of California in French literature has become increasingly prevalent in the past twenty years. The American West Coast, and particularly the metropolis of Los Angeles, do not conform to an established portrait of the United States centered on New York, Chicago, and the South. This article presents three literary interpretations of California by French authors and puts them in conversation with common preconceptions on the state: its superficiality, its disconnection, its glamor. Laure Murat (Ceci n’est pas une ville, Citation2016), Jean Rolin (Le Ravissement de Britney Spears, Citation2011), and Maylis de Kerangal (Naissance d’un pont, Citation2010) approach Californian spaces and communities through contrasting proximity to their referential truth and for three different narrative aims: Murat composes a meditative autobiography, Rolin an (absurd) spy thriller, and Kerangal a globalized Western. All three confront the “non-spaces” and “blank zones” that define or threaten their narrative environments, looming deserts reputedly hostile to meaning, beauty, and lived experiences. Each author gives particular care to the spatial systems borne of a culture that values diversity, fame, money, and the car.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.007 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".