From crisis to comfort : contemporary bestsellers and the French Middlebrow’s narrative of recovery
Bibliographic record
Abstract
The present article proposes an account of the contemporary French Middlebrow through the study of a corpus of bestselling novels. I identify a recurring motif in the bestsellers of the Sarkozy years (2007-2012), a political period marked by debates on national identity and immigration, and thus pertinent to questions on the social imaginary and national representation. The findings demonstrate that the majority of the bestsellers representing contemporary France portray a relationship between a “foreign” character and a depressed or alienated French protagonist. A comparative analysis of the expressions of this theme establishes three distinct categories: firstly, escapist “lowbrow” narratives, by writers such as Marc Levy and Guillaume Musso, where a French expatriate finds salvation abroad thanks to a relationship with an Anglophone character; secondly, “highbrow” narratives of failure (by Michel Houellebecq and Marie Ndiaye) where the protagonist’s relationship with a foreigner increases anxiety or is abandoned; thirdly, “Middlebrow” narratives of recovery (by Muriel Barbery, David Foenkinos and Anna Gavalda) where the French protagonist falls in love with a foreign character within France and is rehabilitated. These three categories provide disparate models for understanding and approaching the problems inherent to contemporary life such as the atomization of traditional social groups. Their comparison puts into relief the core characteristics and function of contemporary French middlebrow fiction.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.019 | 0.017 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".