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Record W3140359023 · doi:10.3138/ecf.33.3.329

Reading Lovelace’s “Rosebud”: Credits, Debits, and Character in Samuel Richardson’s <i>Clarissa</i>

2021· article· en· W3140359023 on OpenAlexvenueno aff
Kathryn Blakely

Bibliographic record

VenueEighteenth-Century Fiction · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHistorical Economic and Social Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGenerosityCharacter (mathematics)Reading (process)PhilosophyReputationLiteratureLawArtTheologyLinguisticsPolitical scienceMathematics

Abstract

fetched live from OpenAlex

Early in Samuel Richardson’s Clarissa (1748), Lovelace boasts of not raping a seventeen-year-old whom he identifies as “his Rosebud.” While critical references to Rosebud are now rare, her presence preoccupied early readers who were so impressed by Lovelace’s generosity that they could scarce believe his later actions toward Clarissa. Although Lovelace acknowledges that years of criminal behaviour have destroyed his reputation, he nevertheless fantasizes that such “generosity” might establish an economy of credits and debits whereby one non-rape can count against a future sexual assault. While Lovelace’s fantasy fails on multiple levels—he invokes the logic of double-entry bookkeeping only to misunderstand it, and his non-rape of Rosebud is, of course, not actually generous at all—it offers a paradigm for understanding Richardson’s broader approach to character. As even Lovelace recognizes, not raping Rosebud can never render him innocent in a larger sense. Returning to Rosebud allows us to read Clarissa as a novel in which character remains fixed, even if it takes hundreds of pages to fully unfold.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.754
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.202
Teacher spread0.183 · 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 teacher head, 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
Published2021
Admission routes1
Has abstractyes

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