Bibliographic record
Abstract
The example of the nineteenth-century literary dandy offers a strategy for transcending social, class and gender barriers through fashion. In this article, I demonstrate that writers, from Eugène Sue to Charles Baudelaire and Rachilde, used representations of the dandy’s androgyny and luxury as a means of overcoming the subordination of the literary domain to capitalist practices. The dandy’s inevitable narrative punishment through death and disgrace also provides release from the tension stemming from the ideological shift in men’s sartorial practices from ostentatious garb to sober and more ‘democratic’ clothing at the end of the eighteenth century. I argue that the dandy’s anti-normative behaviour is a heroic act, perceived and represented by his literary ‘parents’, when both capitalist and political discourses propagate a spurious equality and impose a misleading uniformity in dress on post-Revolution French society. The dandy’s excesses allow modern readers to decipher the writers’ attempt to bridge the gap between social appearances and political reality. For early nineteenth-century writers, the dandy could only be a social climber and a criminal. However, as the century closes, writers begin to appreciate his counter-discursive impact.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.008 | 0.020 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".