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Understanding the Gaps: Four Archetypes of 1790s Gowns

2016· report· en· W2753278688 on OpenAlexaff
Anne Bissonnette

Bibliographic record

Venuenot available
Typereport
Languageen
FieldArts and Humanities
TopicHistorical Studies of British Isles
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsArchetypeModernityIdealismPeriod (music)PoliticsTransition (genetics)AestheticsHistorySociologyArtEpistemologyLiteratureLawPhilosophyPolitical science

Abstract

fetched live from OpenAlex

This research is a component of a larger project investigating a particular moment of transition in the history of fashion, the 1790s in Europe and America, asking how, in an age imbued with idealism, fashion's visual rhetoric could reflect and effect changes in society. In order to analyze dress of this period, the first step was to find, identify and carefully examine surviving gowns and visual sources in France, England, Scotland and the United States of America to reassess the stereotypical understanding of this complex decade that marked the beginning of modernity in dress. A micro-level analysis, the research addresses the gap between the conventional eighteenth-century silhouette to the neoclassical one and isolates four different archetypes of gowns. It provides a base from which to apply a more theorized macro-level analysis that will observe the interactions of dress within the political, philosophical, artistic and economic changes taking place in society.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.293
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.394
GPT teacher head0.286
Teacher spread0.108 · 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 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
Published2016
Admission routes1
Has abstractyes

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