Devious, dashing, disturbing : fallen men in Victorian novels, 1860-1900
Bibliographic record
Abstract
This dissertation questions conventions of Victorian narrative and gender by examining the character of the fallen man as an identifiable literary persona. Fallen men are characterized by their sexuality and conscienceless actions. Their fallenness is contingent on their perceived social standing and genteel expectations. Two popular assumptions about Victorian novels---the gendered specificity of the fallen woman and the propriety of narrative closure---are threatened by the presence of fallen men. While a fallen woman and her miserable fate warn women of the irrevocability of sexual mishaps, fallen men caution readers that the everyday vices to which they may succumb opium, gambling, scientific experimentation, and, later in the century, dandyism---could lead to dire consequences, such as social alienation and unnatural death. Each of these vices represents a threat to Victorian social norms: opium addicts cannot distinguish between innocence and guilt; gamblers highlight the instability of capital and the desperate state of some aristocrats; mad scientists destabilize conceptions of truth; dandies question both rigid notions of masculinity and heterosexuality. Both appealing and evil, fallen men challenge paradigms of hero and villain. Sexually virile, these men also inadvertently save compromised women by suffering untimely deaths.
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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) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.018 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".