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Record W2091233573 · doi:10.1353/elh.2007.0034

Knowing Love: The Epistemology of Clarissa

2007· article· en· W2091233573 on OpenAlexaff
Katherine Binhammer

Bibliographic record

VenueELH · 2007
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Studies on Reproduction, Gender, Health, and Societal Changes
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsNarrativeFemininityBourgeoisieIdeal (ethics)IdeologyAestheticsOrder (exchange)Plot (graphics)LiteratureGender studiesSociologyHistoryArtPhilosophyPoliticsEpistemologyPolitical science

Abstract

fetched live from OpenAlex

My essay focuses on the eighteenth-century gender revolution, in particular, how the obsessive retelling of seduction narratives provided contesting narratives for knowing love. Love's plot changes with the emergence of bourgeois ideology, a change which many feminist scholars interpret as negative for women. In doing so, scholars read late eighteenth-century seduction narratives as always already reflecting the nineteenth-century ideal of passive desexed femininity. My essay focuses on Samuel Richardson's paradigmatic novel Clarissa in order to demonstrate that Clarissa's multiple narratives provide contesting epistemologies. Clarissa shows that the ideal of passive femininity was not the only and inevitable outcome of the gender revolution and that the multiple plots in the novel reflect the heterogeneous terrain for knowing love in the mid-eighteenth century.

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)0.005
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0130.056
Scholarly communication0.0130.011
Open science0.0020.007
Research integrity0.0040.006
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 head0.069
GPT teacher head0.285
Teacher spread0.217 · 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 designTheoretical or conceptual
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

Citations8
Published2007
Admission routes1
Has abstractyes

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