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The Novel and Censorship in Late-Victorian England

2013· book· en· W2630805780 on OpenAlexaff
Barbara Leckie

Bibliographic record

VenueOxford University Press eBooks · 2013
Typebook
Languageen
FieldArts and Humanities
TopicThomas Hardy Literature Studies
Canadian institutionsCarleton University
Fundersnot available
KeywordsCensorshipInterrogationLawLiteratureHistoryArtPolitical science

Abstract

fetched live from OpenAlex

The last two decades of the nineteenth century saw an expansion of print as well as a new freedom of the press; such expansion produced a corresponding movement to suppress such freedom and to censor print. This essay explores the efforts of Oscar Wilde, Thomas Hardy and Grant Allen to redefine the censorship debates in the prefaces to their novels. Often overlooked as a forum for the interrogation of censorship, prefaces manifest not only the complexities of the pressures on novelists to regulate what they wrote but also their efforts to resist those pressures. Legal censorship existed, of course, but Wilde, Hardy, and Allen did not target those forms of control. Instead, they registered the network of pressures arising out of the contexts in which their writing was produced, received, and marketed. Those pressures created varied forms of censorship that determined what could and could not be represented in the novel.

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)0.002
metaresearch head score (Gemma)0.004
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: Other
Teacher disagreement score0.060
Threshold uncertainty score0.120

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0130.027
Scholarly communication0.0100.005
Open science0.0010.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0060.001

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 head0.022
GPT teacher head0.176
Teacher spread0.154 · 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

Citations4
Published2013
Admission routes1
Has abstractyes

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