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Eighteenth-Century Wrecking Revisited

2022· book-chapter· en· W4296613052 on OpenAlexaboutno aff
David Cressy

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicColonialism, slavery, and trade
Canadian institutionsnot available
Fundersnot available
KeywordsLegislationQuarter (Canadian coin)Period (music)Political scienceScholarshipState (computer science)HistoryLawEconomic historyArchaeologyArt

Abstract

fetched live from OpenAlex

Abstract Classic accounts of wrecking focus on Hanoverian Cornwall and deal primarily with episodes from the late eighteenth century. This chapter concentrates on the neglected period before 1750 and presents material from several coastlines. It builds on research in the early modern era to examine shoreline activities in a period of social, economic, and legal change. Engaging with current scholarship, it introduces fresh evidence to reveal the social breadth of participation in wrecking, as shore workers contended with their masters and betters, countrymen vied with mercantile interests, and Customs officers impounded dutiable goods. A growing volume of shipping raised the stakes and expanded opportunities. Coastal conflicts may have become more common, and more riotous, while popular culture depicted wreckers as plunderers ‘blest with fortune’s store’. The legal environment was transformed by legislation in 1714 that threatened fines and imprisonment for anyone who boarded wrecks without permission or impeded the saving of their goods. A much harsher law in 1753 railed against the ‘wicked enormities’ of those who stripped shipwrecks and made unauthorized wrecking a felony punishable by death. The courts of the Admiralty played a lesser role, as Quarter Sessions, Assizes, and newspapers generated more evidence. The state’s demands for revenue from Customs became more aggressive, sometimes backed by troops, while manorial proprietors continued to secure their share. It was in this period that the word ‘wrecker’ first appeared. Charges of ‘barbarous’ behaviour continued, but with no more justification than before. A brief Conclusion ties it all together.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.087
Threshold uncertainty score0.172

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0160.026
Scholarly communication0.0070.006
Open science0.0010.004
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0130.001

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 head0.032
GPT teacher head0.285
Teacher spread0.254 · 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 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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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