Romantic Heredity: Degeneration, Form, and Pathological Readings of ‘The Triumph of Life’
Bibliographic record
Abstract
In ‘The Triumph of Life’, Percy Shelley uses biologically charged language to discuss political and aesthetic heredity. Metaphors of degeneracy, forgetting, and physical infirmity are in turn taken up by the critical reception of the poem after Paul de Man, whereby the fragment is treated by critic-physicians who diagnose the chronic condition of difficulty, expressed through pathological language. Yet in his last work, Shelley engages with romantic life sciences to explore physical, intellectual, political, and aesthetic heredity and what it means to pass on, proto-genetically, aspects of culture and the body by staging an encounter with Life outside the purview of human time and history. He thus engages contemporaneous thinking on reproduction, inheritance, and the life sciences on a subject and a formal level to produce a meditation on heredity through intentional, and not accidental, form. I will think about the poetic fragment as an impasse (Marjorie Levinson) and as a genre of the present (Lauren Berlant), to close read Shelley’s engagement with concepts of heredity. These are linked by his poetics and his scientific inquiry through his explosive use of simile, bringing experimental images into provocative relation, and through resisting generic readings through the instigation of poetic inquiry.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.055 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".