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Record W1998393045 · doi:10.2307/3735510

Discovering the Subject in Renaissance England

2000· article· en· W1998393045 on OpenAlexaff
Constance Jordan, Elizabeth Hanson

Bibliographic record

VenueThe Modern Language Review · 2000
Typearticle
Languageen
FieldArts and Humanities
TopicLiterature: history, themes, analysis
Canadian institutionsQueen's University
Fundersnot available
KeywordsThe RenaissanceSubject (documents)HistoryArtClassicsArt historyLibrary scienceComputer science

Abstract

fetched live from OpenAlex

When Hamlet complains that Guildenstern 'would pluck out the heart of [his] mystery', he imagines an encounter that recurs insistently in the discourses of early modern England. The struggle by one man to discover the secrets in another's heart is rehearsed not only in plays but in legal records, correspondence, philosophical writing and contemporary social description. In this book Elizabeth Hanson argues that the construction of other people as objects of discovery signalled a reconceptualizing of the 'subject' in both the political and philosophical sense of the term. She examines the records of state torture, plays by Shakespeare and Jonson, 'cony-catching' pamphlets and Francis Bacon's philosophical writing, to demonstrate that the subject was both under suspicion and empowered in this period. Her account revises earlier attempts to locate the emergence of modern subjectivity in the Renaissance, arguing for a more nuanced and localized understanding of the relationship with its medieval past.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.100
Threshold uncertainty score0.199

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0070.010
Science and technology studies0.0060.019
Scholarly communication0.0090.006
Open science0.0010.003
Research integrity0.0020.002
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 head0.017
GPT teacher head0.234
Teacher spread0.217 · 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
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

Citations53
Published2000
Admission routes1
Has abstractyes

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