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Record W4211234451 · doi:10.32920/ryerson.14655939.v1

Reading Dress: Fashion and Friendship in A Little Princess And Anne Of Green Gables

2021· preprint· en· W4211234451 on OpenAlexaff
Jaclyn Marcus

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldArts and Humanities
TopicFashion and Cultural Textiles
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsFriendshipMirroringReading (process)Identity (music)SociologySemioticsClosenessArtGirlLiteratureAestheticsPsychologySocial sciencePhilosophyEpistemology

Abstract

fetched live from OpenAlex

This Major Research Project (MRP) argues that fashion is a key tool for the critical examination of textual and visual works. Specifically, this research illustrates fashion’s impact on the social identities of young female protagonists in early-twentieth-century adolescent literature, through a comparative literary study of A Little Princess by Frances Hodgson Burnett and Anne of Green Gables by L.M. Montgomery. Engaging theories of fashion, literature, and girl culture, as well as theories of semiotics and fashion diffusion, dress is shown to be instrumental in developing episodes of closeness and friendship for the protagonists in these novels, along with moments that may isolate them. This MRP examines the illustrations and accompanying textual descriptions found in the 1905 (London) and 1908 (Boston) editions of each work in order to expose fashion’s mirroring and shaping of social identity; ultimately, this study reveals the tension between fashion’s ability to both cement and subvert dominant cultural norms and ideals at the turn of the 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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.007
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.042
GPT teacher head0.251
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
GenreOther

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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