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Record W4239275046 · doi:10.32920/ryerson.14649996.v1

Crowned sisters: object analysis of court dress during Queen Alexandra and Empress Marie Feodorovna's influential reigns

2021· preprint· en· W4239275046 on OpenAlexaboutno aff
Elizabeth Emily Mackey

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldArts and Humanities
TopicFashion and Cultural Textiles
Canadian institutionsnot available
Fundersnot available
KeywordsQueen (butterfly)LawHonourSociologyHistoryPolitical science

Abstract

fetched live from OpenAlex

This Major Research Paper examines female court dress regulations during Queen Alexandra of England and her younger sister, Empress Marie Feodorovna of Russia’s tenures as societal heads during the late nineteenth and early twentieth century. Through object analysis of a court gown of Queen Alexandra’s from the Royal Ontario Museum, and a Russian Maid of Honour’s court gown from The Metropolitan Museum of Art, this research compares how each nation utilized court dress to express wealth, and if the court dress of each nation could communicate the wearer’s court rank within a foreign court. While both nation’s court dress communicated wealth, the motives were different: England’s court dress was highly influenced by fashion trends, whereas Imperial Russian court dress was unchanging in its appearance as its primary purpose was to display a national character. Combining the analysis of each court gown with secondary research and the theory of Thorstein Veblen regarding luxury dress, this paper concludes that each nation’s court dress was highly communicative of a wearer’s rank and wealth.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.216
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0130.000

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 head0.030
GPT teacher head0.245
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 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
Published2021
Admission routes1
Has abstractyes

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