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Record W2976171441 · doi:10.3138/ecf.32.1.31

Plague’s Ecologies: Daniel Defoe and the Epidemic Constitution

2019· article· en· W2976171441 on OpenAlexvenueno aff
Christopher F. Loar

Bibliographic record

VenueEighteenth-Century Fiction · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicYersinia bacterium, plague, ectoparasites research
Canadian institutionsnot available
Fundersnot available
KeywordsPlague (disease)Isolation (microbiology)ConstitutionHistoryVulnerability (computing)Natural (archaeology)Environmental ethicsGeographyLawPolitical scienceAncient historyPhilosophyBiologyComputer securityArchaeologyComputer science

Abstract

fetched live from OpenAlex

Daniel Defoe’s plague writings, particularly A Journal of the Plague Year and Due Preparations for the Plague (both 1722), imagine an ecology of vulnerability. Plague epidemics are natural disasters that serve as reminders of the human body’s absolute dependence on non-human things. For Defoe and many of his contemporaries, the interpenetration of the body and its non-human surroundings make absolute security and immunity impossible. Defoe’s writings turn away from fantasies of isolation and quarantine and instead treat plague both as a memento mori and as a natural phenomenon to mitigate and manage. Drawing implicitly on early work in quantitative social sciences, Defoe’s texts treat the city as an ecological system that can be made more responsive to emergent outbreaks of epidemic illness through the use of accurate information and an awareness of probability. Understood in this way, Defoe’s plague writings are not merely representations of disease but should be seen as crucial components in information networks that seek to mitigate natural disasters.

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)0.009
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: none
Teacher disagreement score0.011
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.015
Scholarly communication0.0080.008
Open science0.0010.003
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0040.001

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 head0.006
GPT teacher head0.236
Teacher spread0.230 · 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

Citations7
Published2019
Admission routes1
Has abstractyes

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Same venueEighteenth-Century FictionSame topicYersinia bacterium, plague, ectoparasites researchFrench-language works237,207