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Record W2085495510 · doi:10.1353/ecf.2012.0016

Opening the Phosphoric "Envelope": Scientific Appraisal, Domestic Spectacle, and (Un)"Reasonable Creatures" in Edgeworth's Belinda

2012· article· en· W2085495510 on OpenAlexvenueno aff
Nicole M. Wright

Bibliographic record

VenueEighteenth-Century Fiction · 2012
Typearticle
Languageen
FieldArts and Humanities
TopicHistory of Science and Natural History
Canadian institutionsnot available
Fundersnot available
KeywordsSpectacleEnlightenmentCreaturesHarmony (color)Scottish EnlightenmentSuperstitionEmpiricismSociologyEpistemologyPhilosophyHistoryArtPolitical scienceLawTheologyArchaeologyVisual arts

Abstract

fetched live from OpenAlex

Maria Edgeworth's novel Belinda (1801) has received increasing attention in recent years from scholars interested in the author's pedagogical methods (introduced by Edgeworth and her father Richard Lovell Edgeworth in the treatise Practical Education [1798]). Yet there has been little sustained critical assessment of the novel's scenes of empirical inquiry, specifically the two phosphoric spectacles, or attention to how these scenes reflect late-Enlightenment debates and Edgeworth's call for a significant revamping of the period's didactic scientific literature. Far from disavowing the value of all emotional response in favour of a frigid adherence to empirical inquiry, Edgeworth's characters show that empiricism can bolster domestic harmony and strengthen emotional bonds within the household. Edgeworth responds to contemporary debates regarding the use of spectacle in teaching science, suggesting that proper scientific education liberates those benighted by superstition and societal prejudices. The scientific method's appeal lies in its transformative effect on the novel's characters, as it generates a shared empirically grounded discourse, fostering communication between characters differing in race, social rank, education, or age.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.391
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.231
Teacher spread0.215 · 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.

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

Citations4
Published2012
Admission routes1
Has abstractyes

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