Bibliographic record
Abstract
My dissertation offers a new entry point into Victorian fiction’s well-documented concern with the credit economy by calling attention to inheritance as a mode of capitalist exchange and subject formation that, although pervasive, has been under-examined. I argue that Victorian novels interrogate the assumption that intergenerational succession is a timeless, natural institution that remains aloof from the psychic and moral dangers commonly associated with financial speculation. My detailed readings of Dickens’s Our Mutual Friend (1864-5), Collins’s Armadale (1866), and Eliot’s Middlemarch (1871-2) demonstrate how their juxtapositions of stockjobbers and gamblers with expectant heirs and testators not only figure inheritance’s alliances with finance but also uncover its intrinsically speculative logic. Through this recurring comparison, which I call “relational speculation,” these novels imbricate the abstracting logics of credit, risk, and contract with the morally and affectively imbued structures of family, marriage, and property. In focusing on relational speculation, I complicate critical tendencies to view the persistence of inheritance plots in nineteenth-century novels as mere “convention” or as a kind of infrastructural holdover. Instead, I illuminate this persistence by tracing tensions in eighteenth- and nineteenth-century popular, legal, and political accounts of succession and bequest, showing how they struggle to redefine these models of intergenerational transmission both through and against the precepts of capitalism, contractual individualism, and corporate personhood. I suggest that Dickens, Collins, and Eliot foreground the paradoxes implicit in these efforts via the trope of relational speculation, which pervades their plots, figures, and modes of narration. Their novels question the speculative and corporate-like relationship these models of inheritance construct between testators and would-be heirs by depicting identity mistakes and impersonations, fantasies of posthumous ownership, fears of inherited liability, and constraining dead hands. Relational speculation thus reveals the substitutive and proleptic structures of identity, ownership, and responsibility latent to speculation and inheritance alike. Insofar as it prompts these novels both to ironize some of inheritance’s key narrative conventions and to seek ways of controlling their own implicitly speculative dynamics, relational speculation ultimately plays an important role in shaping their formal as well as thematic concerns.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.029 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".