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Record W3036066953 · doi:10.1353/vcr.2019.0057

Horse-Racing Fraud in Victorian Fiction

2019· article· en· W3036066953 on OpenAlexvenueno aff
Nancy Henry

Bibliographic record

VenueVictorian review · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicAmerican Sports and Literature
Canadian institutionsnot available
Fundersnot available
KeywordsHorse racingTrophyCompetition (biology)HistoryLawOddsCriminologySociologyPolitical scienceEntertainment

Abstract

fetched live from OpenAlex

Horse-Racing Fraud in Victorian Fiction Nancy Henry (bio) In his account of English horse racing, A Mirror of the Turf (1892), Louis Henry Curzon writes: There is no other business, perhaps, which offers so many opportunities for successful fraud as horse-racing, and that for the best of reasons: the chicanery that is prevalent does not render those who practice it amendable to the criminal law, turf crimes being without the pale of legal action. (271)1 Curzon reflects that frauds in the late nineteenth century are more subtle and less violent than in the past, when a horse might be “ ‘nobbled’ or ‘got at’ by some person hired for the purpose, or it might be lamed by the farrier, or perhaps poisoned by a stable attendant” (272). In contrast, the “coups” of his own time are planned over months or years, as when bookmakers purchase horses in order to manipulate their odds across multiple races. Such scams may be impossible to detect, much less punish. He concludes that “turf frauds of many kinds, but especially those kinds which entail no penal consequences, are plentiful enough even at the present time” (300).2 Victorian and contemporary historians have established the changing nature of racing fraud, which became more businesslike as the sport became more commercialized.3 Victorian horse-racing fiction represents a distinctive subculture at the intersection of athletic competition and local and global economies of betting. J. Jeffrey Franklin analyzes gambling as “part of the Victorian discourse of money, [treated] as one among the other channels through which capital was circulated in nineteenth-century Britain” (34–35). I argue further that a focus on horse racing, and on fraud in particular, in Victorian fiction contributes not only to the histories of racing and gambling but also to the history of finance and financial fiction. Writers of fiction were particularly drawn to those earlier forms of fraud mentioned by Curzon, such as poisoning and laming, which could only be carried out by someone intimate enough with the horse to get close and do harm. Such acts of sabotage were motivated by vengeance—usually against the owners of the horse. The elements of class conflict and personal vendetta played into the overall themes of Victorian fiction. The problem of how to identify the perpetrator was consistent with that of other financially themed novels. Swindlers such as Charles Dickens’s Merdle in Little Dorrit (1855–57) [End Page 235] or Anthony Trollope’s Dobbs Broughton (also a horse player) in The Last Chronicle of Barset (1866–67) or Augustus Melmotte in The Way We Live Now (1875) disguise their scams through false identities and elaborate schemes. In contrast, tampering with a horse to sabotage a race, on which great sums of money might be wagered, depends on the simple fact that horses cannot testify. Fiction has the capacity to examine the psychology of the saboteur as well as the experience of the horse. In this respect, examining frauds that involve tampering with the equine athlete opens up the study of financial fiction to the realm of animal studies.4 That Curzon sought a variety of terms—fraud, chicanery, and crime—to describe cheating in racing suggests the difficulty of definitions. The term fraud is expansive, encompassing many possible scenarios of dishonest behaviour. Chicanery seems quaint, and crime is inaccurate where the law is not involved. Within sports generally, Graham Brooks, Azeem Aleem, and Mark Button see fraud as a subset of corruption and offer a useful definition: fraud “is based on deception with the intention of securing some advantage—immediate or in the future—and depriving a third party such as individual(s), a small group of people or organisation of honest services or benefits at the expense of other individuals and organisations” (18). I keep this definition in mind while employing the term fraud in cases where a saboteur intends to deprive an owner of a sound horse, and, consequently, to defraud of their money the people who bet on that horse. Furthermore, such fraud may symbolically target an entire class of wealthy horse owners; crucially, it also physically harms the animal, which may or may not recover. With...

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.879
Threshold uncertainty score0.970

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0310.001

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.

Opus teacher head0.009
GPT teacher head0.221
Teacher spread0.212 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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Same venueVictorian reviewSame topicAmerican Sports and LiteratureFrench-language works237,207