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Milton and the Uses of Stupidity

2023· article· en· W4385760230 on OpenAlexaff
Jason Peters

Bibliographic record

VenueMilton Studies · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicSeventeenth-Century Political and Philosophical Thought
Canadian institutionsBooth University College
Fundersnot available
KeywordsStupidityInnocenceSkepticismWonderRelation (database)CriticismPhilosophyFace (sociological concept)Agency (philosophy)AestheticsLiteratureEpistemologyPsychoanalysisArtPsychology

Abstract

fetched live from OpenAlex

ABSTRACT When we call someone or something “stupid,” it is an insult. So, when Milton’s narrator in Paradise Lost says Satan is momentarily rendered “stupidly good” at the sight of Eve, we read it the same way: the devil’s brief redemption is downplayed while his stupidity is emphasized. This essay argues that privileging rational human agency and virtuous freedom over more aesthetic and potentially “stupid” forms of wonder makes it hard to recognize the unsettling relation between Satan’s experience and the intellectual innocence that was prized by experimentalists such as Francis Bacon. It also suggests that Milton’s reflections on stupidity offer a helpful way to think about literary criticism; far from being a bad thing, Satan’s stupidity is a form of innocence that emerges from skepticism and critique—a kind of astonishment that brings us face to face with our own limits, not only as readers and students, but also as scholars and teachers.

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)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.013
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0130.078
Scholarly communication0.0110.007
Open science0.0010.007
Research integrity0.0030.005
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 head0.210
GPT teacher head0.330
Teacher spread0.119 · 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 designTheoretical or conceptual
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

Citations0
Published2023
Admission routes1
Has abstractyes

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