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Record W2992684869 · doi:10.1353/his.2019.0059

Shoplifting in Eighteenth-Century England by Shelley Tickell

2019· article· en· W2992684869 on OpenAlexvenueno aff
Richard C. Ward

Bibliographic record

VenueHistoire sociale · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHistorical Economic and Social Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCommitLawConvictHistoryPleasureSociologyArt historyArtPolitical sciencePsychology

Abstract

fetched live from OpenAlex

Reviewed by: Shoplifting in Eighteenth-Century England by Shelley Tickell Richard Ward Tickell, Shelley – Shoplifting in Eighteenth-Century England. Woodbridge, UK: The Boydell Press, 2018. Pp. 236. In April 1805, Margaret Berry and Jane Scott were put on trial at the Old Bailey for stealing 13 yards of printed cotton from a linen draper’s shop. The shop assistant had suspicions about the women from the moment they came in. When asked why he had not attempted to pre-empt the theft, the shop assistant bluntly responded, “Because I wanted to make it a capital offence.” When reproached for this by the counsel for the defence, the shop assistant was unrepentant: [End Page 418] Q. Your Christian charity did not prompt you to tell them you wanted them to commit a felony, that you might have the pleasure of prosecuting? A. Exactly. (p. 140, fn.69) Eighteenth-century England witnessed the rise of a “Bloody Code”—over 200 laws that stipulated the death penalty, particularly for property crimes that were seen to be on the rise—along with a “consumer revolution” and an unprecedented expansion in retailing. Shoplifting potentially has a lot to tell us about these developments, but in falling at this juncture between the histories of crime, consumption, and retail, it has so far escaped detailed attention. Shoplifting in Eighteenth-Century England brings these three historical fields together in a comprehensive examination of shoplifting between the 1690s and 1820s. The chief sources are the Old Bailey Proceedings (published accounts of the trials held at London’s central criminal court) and manuscript depositions from Northern Circuit assize courts. Forensic quantitative and qualitative analysis is carried out on a sample of 922 shoplifting cases at the Old Bailey (covering the years 1743–1754, 1765–1774, 1785–1789 and 1805–1807) and on 147 shoplifting cases heard at the Northern Circuit between 1726 and 1829. This is supplemented by a qualitative analysis of cases from the Old Bailey Proceedings outside the sample years, along with an impressive variety of other sources, including parliamentary papers, Prosecution Society minute books, business records, retailers’ diaries, newspapers, prints, and novels. Each chapter deals with a specific characteristic of shoplifting: the social profile—class, gender, ages, occupations—of those prosecuted (Chapter 1); the scale, geography, and topography of the crime (Chapter 2); the ways in which shoplifting was perpetrated, prevented, and policed (Chapter 3); what was stolen and for what ends (Chapter 4); the economic impact of the crime on retailers’ livelihoods (Chapter 5); the law on shoplifting as it was enacted, interpreted, and applied (Chapter 6); and public attitudes to the crime (Chapter 7). The book also overlays these characteristics of shoplifting with attention to the differing viewpoints of the offender, the retailer, and the general public, drawing on the criminological theory of “routine activity” as a framework for understanding the relationship between criminal, victim, and social environment. The book offers many important findings. Common myths are dispelled: rather than targeting the finest outlets, which stocked higher value items, the majority of shoplifters favoured smaller, local shops that “were familiar, had fewer staff to detect theft and a clientele among whom their dress and manner would not appear conspicuous” (p. 193). Nor was plebeian emulation of high-end fashions or elite goods the main driving force behind what was stolen; instead, items typically related to popular styles and everyday workwear (p. 124). Simple assumptions are also tested rather than accepted without question. By piecing together the fragmentary evidence available, Tickell suggests that there was no obvious correlation between financial vulnerability and prosecution rates: those whose livelihoods were most threatened by shoplifting did not necessarily prosecute. Some victims of shoplifting responded with passive acceptance, others [End Page 419] with virulent rage (p. 142). Important light is shed on the interaction between criminality, retailing, and consumerism. The increasing affordability of glass in the eighteenth century gave some protection to retailers from the threat of snatch-and-grabs, but as market competition increased, so shopkeepers sought more effective ways of attracting customers, including external displays of goods, resulting in a marked increase in prosecuted cases of external thefts by the early nineteenth century. This provoked one judge...

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.110
Threshold uncertainty score0.219

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0050.004
Scholarly communication0.0040.004
Open science0.0010.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0480.009

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 head0.012
GPT teacher head0.179
Teacher spread0.167 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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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Citations1
Published2019
Admission routes1
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