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Record W2941538543 · doi:10.7202/1069961ar

Epic Poetry and the Origins of Evolutionary Theory

2020· article· en· W2941538543 on OpenAlexvenueno aff
John Holmes

Bibliographic record

VenueRomanticism and Victorianism on the Net · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicHistory of Science and Natural History
Canadian institutionsnot available
Fundersnot available
KeywordsErasmus+PoetryDarwin (ADL)VisionLiteratureEPICPhilosophyArtArt historyHistoryTheology

Abstract

fetched live from OpenAlex

In this article I will examine how Erasmus and Charles Darwin responded to the epic tradition in their writings, and how the legacy of epic was worked into their respective evolutionary visions. Erasmus Darwin formulated a brief sketch of his evolutionary theory in prose in his medical textbookZoonomia, but when he came to flesh out his conception of evolution in imaginative and empirical detail he turned to verse. His poemThe Temple of Nature, published posthumously in 1803, self-consciously evokes epic conventions and engages intertextually with Milton, Lucretius and Ovid in particular. One of the poems that Erasmus Darwin replied to in his verse –Paradise Lost– was by Charles Darwin’s account his constant companion during his voyage on the Beagle. Through exploring how both Darwins responded to Milton’s vision of Creation, and to the counter-visions offered by other epic poets and by Satan within Milton’s own poem, it is possible to see how fundamental epic poetry was to the generation of evolutionary theory and the forms it came to take.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.996
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0040.027
Scholarly communication0.0050.005
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.020
GPT teacher head0.192
Teacher spread0.172 · 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.

Study designTheoretical or conceptual
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
Published2020
Admission routes1
Has abstractyes

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