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Record W2323921088 · doi:10.3138/ecf.28.3.501

“The Greatest Appearance of Truth”: Telling Tales with Thomas Holcroft

2016· article· en· W2323921088 on OpenAlexvenueno aff
Eliza O’Brien

Bibliographic record

VenueEighteenth-Century Fiction · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicNarrative Theory and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsTruth tellingOmnipotenceMemoirRelation (database)PhilosophyEpistemologyPragmatic theory of truthTest (biology)LiteraturePsychologyAestheticsPsychoanalysisArtComputer science

Abstract

fetched live from OpenAlex

The eighteenth-century radical Thomas Holcroft (1745–1809) devoted himself to communicating truth in all his writings. But to what extent is this dedication to truth-telling undermined by Holcroft’s use of deceit and duplicity to test the omnipotence of truth, especially when deceit threatens to overpower truth? In this article, I examine a series of scenes in Holcroft’s plays and novels wherein truth is not always adequately expressed in language. As a result, performance gains importance. Holcroft develops an increasingly subtle understanding of the relation between truth and the modes of its communication. Performance, even as it may seem to destabilize speech, can be used to intensify it and ultimately to clarify the transmission of truth, which is Holcroft’s great aim. By the end of his career, in his final novel Memoirs of Bryan Perdue (1805) Holcroft’s understanding of the efficacy of clear speech and performance is strengthened and developed by a new appreciation of what the body of the truth-teller, silent or speaking, can convey.

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: Empirical · Consensus signal: none
Teacher disagreement score0.022
Threshold uncertainty score0.044

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 studies0.0120.029
Scholarly communication0.0060.005
Open science0.0010.003
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0030.001

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 head0.012
GPT teacher head0.192
Teacher spread0.179 · 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

Citations2
Published2016
Admission routes1
Has abstractyes

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