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Record W4242409670 · doi:10.24908/iqurcp.7956

The Battle of the Dubyas: Romantic vs. early modern version

2017· article· en· W4242409670 on OpenAlexvenueno aff
J. Rosel Kim, Lucas Tingle

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicModernist Literature and Criticism
Canadian institutionsnot available
Fundersnot available
KeywordsGeniusAndrogynyRomanceLiteratureBattleIdeologyRomanticismCriticismSubject (documents)PhilosophyStyle (visual arts)ArtPsychoanalysisHistoryPsychologyPoliticsLawMasculinity

Abstract

fetched live from OpenAlex

A creative assignment for an Introductory Literary Theory and Criticism course, The Battle of the Dubyas: Romantic vs. early Modernist version depicts a fictional dialogue between the Romantic poet William Wordsworth and modern writer Virginia Woolf. The informal nature of a dialogue allows for a heated debate between the two theorists, where their distinct style of speaking—Woolf with her many dashes and Wordsworth with his complete sentences—convey the periodical and ideological differences. The first subject of the debate is the topic of androgyny, where Woolf explains the demerits of confining writing to a single­sexed medium—whether it be an overtly direct writing, or covertly complicated one—and chides Wordsworth for being too masculine in his thought. The second topic arrives at the issue of material conditions needed for literary genius—where Wordsworth’s notion of the Poet transcending all physical obstacles is debunked and silenced by Woolf’s fictional account of Shakespeare’s sister, Judith. Between the opposing stances of each theorist’s views on gender divide in writing and nature vs. nurture in breeding genius, Woolf’s ideals of androgyny and material necessity for genius triumph that of Wordsworth’s arcane and masculine views on natural genius of the Poet.

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)0.003
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 score0.013
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.023
Scholarly communication0.0130.004
Open science0.0010.003
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0080.001

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 head0.101
GPT teacher head0.337
Teacher spread0.236 · 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
Published2017
Admission routes1
Has abstractyes

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