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Record W2790985498 · doi:10.3138/ecf.30.3.395

“Labouring in Suspense”: Paying Attention to Providence in Samuel Richardson’s <i>Clarissa</i>

2018· article· en· W2790985498 on OpenAlexvenueno aff
Candace Cunard

Bibliographic record

VenueEighteenth-Century Fiction · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicLiterature: history, themes, analysis
Canadian institutionsnot available
Fundersnot available
KeywordsReading (process)Interpretation (philosophy)LiteraturePsychologyPhilosophyPsychoanalysisEpistemologyArtLinguistics

Abstract

fetched live from OpenAlex

This article examines the connection between suspense, providential anxiety, and the types of reading practices that are both represented in and required by Samuel Richardson’s Clarissa (1747–48). While some scholars point out that suspense and providence produce similar states of anxious pas sivity in readers, I argue that Richardson’s techniques for managing sus pense encourage the active—if provisional—interpretation of events still in progress, a process I term “attentive reading.” Not all suspense trains readers in attention, as Lovelace’s manipulative schemes make clear. However, Richardson’s epistolary technique of “writing to the moment,” taken alongside the novel’s editorial apparatus of prefaces, footnotes, and post scripts, simultaneously intensifies readers’ experience of suspense and offers the tools for developing provisional judgments within it. I conclude by reading Clarissa’s “father’s house” letter, and its gradual interpretation by other characters, as a model for the kind of attentive reading that the novel as a whole demands.

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)0.006
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: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.020
Scholarly communication0.0070.004
Open science0.0010.003
Research integrity0.0020.005
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 head0.228
Teacher spread0.211 · 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
Published2018
Admission routes1
Has abstractyes

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