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Record W4408609775 · doi:10.22148/001c.128008

Quantifying the Presence of Ancient Greek and Latin Classics in Early Modern Britain

2025· article· en· W4408609775 on OpenAlexvenueno aff
Margherita Fantoli, Jukka Suomela, Toon Van Hal, Mark Depauw, Lari Virkki, Mikko Tolonen

Bibliographic record

VenueJournal of Cultural Analytics · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical and Literary Studies
Canadian institutionsnot available
Fundersnot available
KeywordsClassicsHistoryAncient GreekAncient historyArt

Abstract

fetched live from OpenAlex

This paper explores the reception of classical works in Early Modern Britain during the hand press era, between the 1470s and 1790s. It investigates canon formation, knowledge transmission, and the integration of digital archives in quantitative book history. The study quantitatively maps changing perceptions of the classical canon across time, offering a panoramic view of 'shifting canons'. The analysis is based on three data archives: the English Short Title Catalogue (ESTC), Early English Books Online (EEBO), and Eighteenth Century Collections Online (ECCO). We conclude that we can observe a “canonization” of the set of classical authors printed in Early Modern England, which is reflected in a significant loss of diversity in publications, despite a general increase of the publication of classical works. Preferences also shift, with ancient Greek authors of the early centuries gaining significantly more space in the 18th century. This finding however is balanced by the observation that the circulation of Ancient Greek editions in the original language does not increase during this time. This multidimensional approach contributes to a comprehensive understanding of the reception of Classics in Early Modern Britain, shedding light on cultural and intellectual transformations.

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)0.001
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0090.013
Science and technology studies0.0010.003
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0000.000
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 head0.067
GPT teacher head0.329
Teacher spread0.262 · 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 designObservational
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
Published2025
Admission routes1
Has abstractyes

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