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Record W4221062727 · doi:10.3390/h11020042

Pietas in Patriam: Milton’s Classical Patriotism

2022· article· en· W4221062727 on OpenAlexaff
Paul Stevens

Bibliographic record

VenueHumanities · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicReformation and Early Modern Christianity
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPatriotismNationalismInternationalism (politics)CiceroPoliticsLiteraturePhilosophyAestheticsClassicsHistoryArtLawPolitical science

Abstract

fetched live from OpenAlex

The subject of this essay is the relation between Milton’s classical patriotism and his English nationalism. It has two principal aims. First, it sets out to examine the degree to which the affective or emotional quality of Milton’s patriotism was shaped by the classics, especially Cicero and Virgil. For all the energy that has gone into studying Milton’s classical republicanism, there has been relatively little interest in that political movement’s central concern with patriotism: few, for instance, have shown much interest in David Norbrook’s acknowledgment that “English republicanism emerged in part as a vehicle for English nationalism.” And second, through this focus on the classical aspect of Milton’s patriotism, it argues that far from being neutralized or undercut, Milton’s nascent nationalism was actually enabled and intensified by his internationalism, an internationalism that is most graphically illustrated by his engagement with Italy and its role in recovering the classics.

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)0.001
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: none
Teacher disagreement score0.004
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.015
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.058
GPT teacher head0.224
Teacher spread0.166 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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