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Record W4396243222 · doi:10.5539/ells.v14n2p13

Charlotte Perkins Gilman’s Evolution of Community Thought: From The Yellow Wallpaper to Herland

2024· article· en· W4396243222 on OpenAlexvenueno aff
Rongfei Wang

Bibliographic record

VenueEnglish Language and Literature Studies · 2024
Typearticle
Languageen
FieldPsychology
TopicAcademic and Historical Perspectives in Psychology
Canadian institutionsnot available
FundersJilin Office of Philosophy and Social Science
KeywordsWallpaperArt historyHistoryArtSociologyComputer science

Abstract

fetched live from OpenAlex

Charlotte Perkins Gilman was a prominent American novelist and feminist, well-known for her works The Yellow Wallpaper and Herland, which have drawn considerable attention from scholars at home and abroad and aroused wide discussion since their publication. In most cases, the former was regarded as a classic of gender politics and the latter, a feminist utopia. Through the detailed analysis of the two works, it can be found that Gilman has interwoven the spirit of community into the two works, considering it as the right path to gaining women’s equality and freedom. In The Yellow Wallpaper, Gilman just implicitly puts forward women alliance as a potential way to liberate women; while in Herland, Gilman describes the harmony between people (women) and the surroundings, between people (women) and people (men), which demonstrates that Gilman is more resolute and more confident in community and cooperation. In the meanwhile, from the two works, it can be found that Gilman’s thought on community is changing and more and more progressive and that the forming of community is a more effective way to contribute to personal growth and development.

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.036
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0180.045
Scholarly communication0.0120.009
Open science0.0010.006
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0040.001

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 head0.016
GPT teacher head0.336
Teacher spread0.320 · 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 designQualitative
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
Published2024
Admission routes1
Has abstractyes

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