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Record W4236514446 · doi:10.3138/ecf.24.4.569

No Dishonour to Be a Pirate: The Problem of Infinite Advantage in Defoe's <i>Captain Singleton</i>

2012· article· en· W4236514446 on OpenAlexvenueno aff
Jeremy Wear

Bibliographic record

VenueEighteenth-Century Fiction · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicAmerican Constitutional Law and Politics
Canadian institutionsnot available
Fundersnot available
KeywordsSingletonScarcityAmbiguityHEROIdeologyCapitalismFantasySociologyLawEconomicsHistoryPolitical scienceLiteraturePhilosophyArtMarket economyLinguistics

Abstract

fetched live from OpenAlex

In Captain Singleton (1720), Daniel Defoe rehearses the ethical and discursive justifications of predatory capitalism. Through an examination of Defoe's economic writings, I illustrate how the author confronts readers with the moral ambiguity of legal trade by comparing the “litteral” pirate Singleton with the “allegorical” pirates of London's central economic institutions. Through this comparison, Defoe places legal trade on an uncertain continuum with piracy. By extension, he explores the problematic necessity of reconciling the hero-outlaw Singleton's piracy to conceptions of national identity predicated on economic expansionism. Defoe suggests this reconciliation is best achieved by understanding trade in terms of “infinite advantage.” This article contextualizes “infinite advantage” as an imaginative projection onto the world of the conditions necessary to sustain infinite trade, and argues that Singleton appropriates this ideology to palliate fears of Hobbesian scarcity. Thus, the novel examines the conditions of scarcity that precipitate predatory trade practices alongside the fantasy of economic infinitude that would make these practices obsolete.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.987
Threshold uncertainty score0.394

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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.

Opus teacher head0.019
GPT teacher head0.280
Teacher spread0.261 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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".

Quick stats

Citations1
Published2012
Admission routes1
Has abstractyes

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