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Wharton’s Living City in “Bunner Sisters”

2022· article· en· W4385454584 on OpenAlexaff
Rita Bode

Bibliographic record

VenueEdith Wharton Review · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicAmerican and British Literature Analysis
Canadian institutionsTrent University
Fundersnot available
KeywordsNovellaAppealContext (archaeology)InterdependenceEcocriticismSociologyUrban planningEnvironmental ethicsAestheticsHistorySocial scienceArtEcologyLiteratureLawPolitical sciencePhilosophyArchaeology

Abstract

fetched live from OpenAlex

Abstract Edith Wharton’s early novella, “Bunner Sisters,” shows the author’s engagement with ecological thinking from early in her career. Despite her sometimes negative comments on cities, Wharton’s fiction reveals the appeal that the urbanscape held for her imagination. An ecocritical approach, informed by urban ecology, traces in “Bunner Sisters” Wharton’s understanding of the city as a dynamic entity made up of multiple interdependencies that include both animate (human and non-human) and inanimate matter. Wharton’s ecological awareness illuminates the sisters’ relationship to their surroundings through their forays into green spaces and engagement with flowers. In Evelina’s case, especially, it illuminates the seductive and detrimental effect of social ideals concerning the marital status of women. More broadly, the sisters’ urban context looks forward to best practices in urban planning. With remarkable prescience, Wharton’s New York in “Bunner Sisters” functions along urban principles aimed at maintaining vibrant cities that align with those espoused by late twentieth-century urban activist Jane Jacobs and subsequently adopted by urban planners and designers.

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)0.001
metaresearch head score (Gemma)0.003
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.084
Threshold uncertainty score0.167

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.005
Science and technology studies0.0030.004
Scholarly communication0.0040.004
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.019
GPT teacher head0.229
Teacher spread0.210 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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