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Record W2033119360 · doi:10.1093/jdh/epv013

The Good Women of Peterhouse: Patriarchal Community, Femininity and University Reform

2015· article· en· W2033119360 on OpenAlexaff
Vednita Carter

Bibliographic record

VenueJournal of Design History · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical Gender and Feminism Studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsFemininityLegendGender studiesPoetryRomanceGirlSociologyPower (physics)ArtAestheticsLiteraturePsychology

Abstract

fetched live from OpenAlex

This article reads a Morris, Marshall, Faulkner & Company stained glass window in light of Victorian reforms extending university education to women. Designed by Edward Burne-Jones and installed in the Senior Combination Room of Peterhouse College in 1870, the window boasts six stained glass panels that together illustrate twelve characters from Geoffrey Chaucer’s The Legend of Good Women. I argue that the beautiful, passive, idealized women the panels represent constitute a discursive response to the social and cultural anxieties raised by the emerging figure of the girl-under-graduate, who was widely understood to threaten the patriarchal structure of the academy. Comparing Chaucer’s poem to Burne-Jones’ design, I contend that both poet and artist defined ideal femininity as an expression of masculine mastery, and a ‘good woman’ as compliant to male authority in love and life. I then frame the ‘goodness’ of the window’s figures within the contemporary discourses levelled against female undergraduate students. Taking surviving archival evidence into account, I interpret the decision to include the window’s visual illustration and material incarnation of fragile femininity within the cloistered, homosocial space of the Combination Room as a defensive one, intended to bolster a masculine community that feared itself besieged by power-hungry women.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.028
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0130.032
Scholarly communication0.0080.003
Open science0.0010.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0070.001

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 head0.144
GPT teacher head0.282
Teacher spread0.138 · 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

Citations3
Published2015
Admission routes1
Has abstractyes

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