Troubling the Tragic Paradigm: Genre and Epigraph in Thomas Hardy’s Tess of the d’Urbervilles
Bibliographic record
Abstract
Abstract The rarely discussed epigraph to Thomas Hardy’s Tess of the d’Urbervilles – ‘Poor wounded name! My bosom as a bed | Shall lodge thee’ – at first seems an odd choice. Tess is usually read as a tragedy; the epigraph’s source, Shakespeare’s The Two Gentlemen of Verona, is a comedy. The speaker of these lines in the play is a woman, the ‘wounded name’ a man’s, and the immediate context one of erotic playfulness as Julia tears up Proteus’s love letter and then tenderly gathers up the fragments. Yet the apparent mismatch works, because it gestures towards both the generic instability of Two Gentlemen, and the novel’s own unstable genre. Hardy recurrently raises the question of how Tess Durbeyfield’s story should be read. Tess’s ‘fall’ is at different times and for different people a fatal blot on her prospects, a venial error, and material for an amusing or satirical story. Novel and heroine hover between genres; generic interpretations are complicated by gender and class. Early reviewers who refused to read Tess as a tragedy may seem wrong-headed and puritanical in hindsight, but they were in some ways more alive to the novel’s generic slippages than many later readers. Hardy at once invokes and unsettles generic models, in his choice of epigraph and throughout the book.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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.
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".