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Record W4391312681 · doi:10.33137/rr.v41i4.32449

“My Own Worst Enemy”: Translating <i>Hamartia</i> in Sixteenth-Century Italy

2019· article· en· W4391312681 on OpenAlexvenueno aff
Bryan Brazeau

Bibliographic record

VenueRenaissance and Reformation · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicRenaissance and Early Modern Studies
Canadian institutionsnot available
FundersEuropean CommissionUniversity of Warwick
KeywordsAdversaryArtComputer scienceComputer security

Abstract

fetched live from OpenAlex

This article considers the ways in which Aristotle’s notion of hamartia (ἁμαρτία) in the Poetics—the tragic fault that leads to the protagonist’s downfall—was rendered in sixteenth-century translations and commentaries produced in Italy. While early Latin translations and commentaries initially translated the term as error, mid-Cinquecento literary critics and theorists frequently used a term that implied sin: peccatum/peccato. Was this linguistic choice among sixteenth-century translators indicative of a broader attempt to Christianize the Poetics? While there were significant attempts on the part of translators and commentators to moralize the Poetics, this study of how hamartia was translated suggests that such interpretations were not Counter-Reformation distortions of Aristotle’s Poetics but rather part of a broader program of cultural translation—expressing the linguistic influence of a religious public, but not necessarily a moralizing interpretation—domesticating the Greek philosopher for an early modern Christian audience.

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)0.006
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0050.014
Scholarly communication0.0050.003
Open science0.0000.003
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0030.001

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 head0.016
GPT teacher head0.215
Teacher spread0.198 · 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
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

Citations0
Published2019
Admission routes1
Has abstractyes

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