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Record W2781738262 · doi:10.3138/ecf.30.2.153

Sociality and Good-Faith Economy in Daniel Defoe’s <i>Robinson Crusoe</i>

2018· article· en· W2781738262 on OpenAlexvenueno aff
Daniel Yu

Bibliographic record

VenueEighteenth-Century Fiction · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Art and Culture Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSocialityFaithNarrativeIndividualismGoodwillReading (process)SociologyMythologyPhilosophyEpistemologyLawPolitical scienceTheologyEconomics

Abstract

fetched live from OpenAlex

Robinson Crusoe (1719) by Daniel Defoe was long hailed as the founding myth of “Economic Man,” with critics until the mid-twentieth century tending to portray the shipwrecked narrator as the exemplar of utilitarian individualism. The novel’s reception among economists from David Ricardo to Karl Marx was largely determined by Jean-Jacques Rousseau’s revisionary reading, which excluded large parts of the narrative from consideration. In revisiting the parts that Rousseau thought extraneous, this essay finds that the character of Crusoe is an eminently social being who relies on the charity of several generous benefactors. Their relationships are notably amicable, constituted by mutual trust and goodwill. As an intimate society, they share gifts and ex change favours without apparent regard for profit-making. In representing them selves as generous friends, they belie the economic realities that support their accumulation of wealth. The Crusoe that emerges from an examination of his symbolic activity is one whose practices of gift-giving are governed less by reason or notions of utility than by powerful symbols and the relations that inhere in them.

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)0.000
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 score0.927
Threshold uncertainty score0.719

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.211
Teacher spread0.196 · 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
Published2018
Admission routes1
Has abstractyes

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