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Record W4234407632 · doi:10.3138/ecf.25.3.557

Hannah More’s Art of Reduction

2013· article· en· W4234407632 on OpenAlexvenueno aff
Andrew J. Heisel

Bibliographic record

VenueEighteenth-Century Fiction · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicReligion and Society Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsRhetoricOrder (exchange)PhilosophyAmbiguityPower (physics)CriticismHierarchyAestheticsEpistemologyLiteratureTheologyArtLawLinguisticsPolitical science

Abstract

fetched live from OpenAlex

Hannah More is widely viewed as a major figure in the rise of evangelicalism, but how she played her role is still in doubt. She can be read as a conservative interested in maintaining social hierarchy or even as a radical who levels social strata by insisting that only spiritual classifications are important. An underlying network of theological uncertainties in More’s writing creates this divide in the criticism of her work. More insists on the plainness of the Bible, but, since readers nonetheless err, she suggests its plainness must first be matched in the reader in order for the text to be understood. She contradictorily indicates that the Bible or morally sound fictional works may improve the reader and that readers must already be purified before a text can have saving effects. On the one hand, this theological ambiguity can be liberating. On the other hand, the Pauline universalizing rhetoric on which More relies, rather than having the salutary impact recently described by philosophers Giorgio Agamben and Alain Badiou, creates a constant interrogation of self and others in order to reduce individual particularity. More’s fiction continually figures forth the need for an “annihilation of the self” that is to be admired for its saving power and yet also pitied for the suffering it creates—suffering which is the vehicle of both that annihilation and attendant salvation.

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)0.007
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 score0.010
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.016
Scholarly communication0.0050.005
Open science0.0010.003
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0100.002

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 head0.014
GPT teacher head0.288
Teacher spread0.275 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

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