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Record W2177496138 · doi:10.5539/ass.v11n28p29

Historiography Analysis of Qing Dynasty Clothing Review in ‘Geng Yi Ji’

2015· article· en· W2177496138 on OpenAlexvenueno aff
Lanlan Yan, Xiangyang Bian

Bibliographic record

VenueAsian Social Science · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicFashion and Cultural Textiles
Canadian institutionsnot available
FundersDonghua UniversityUniversity of Edinburgh
KeywordsHistoriographyChinaClothingConnotationHistory of ChinaHistoryPeriod (music)Shang dynastyAncient historyArtAestheticsPhilosophyArchaeology

Abstract

fetched live from OpenAlex

<p>‘Geng Yi Ji’, written by Eileen Chang, is the important literature for fashion research of the Republic Period of China, and most of scholars in fashion field also focus on this part, they mensioned this article in lots of books. While, there is nearly no literature talk about the fashion of Qing dynasty in ‘Geng Yi Ji’. In fact, compare with the fashion in the Republic Period, the fashion in Qing dynasty is also a mian part of ‘Geng Yi Ji’. This thesis analyzes Eileen Chang’s Qing dynasty fashion review in ‘Geng Yi Ji’ through historiography point, in order to explore certain fashion culture and fashion history in ancient China. The thesis analyzes three fashion reviews of Eileen Chang, briefly including ‘over the course of three hundred years of Manchu rule, women lacked anything that might be refeered to as fashion’, ‘the details of ancient Chinese clothes were completely pointless, such as the soles of cotton shoes inscribed with patterns’, ‘the dissipation of energy on irrevevant matter, marked the attitude toward life of the leisure class in China, such as the three or more pippgs and trimmings on coats’. Through the historiography analysis, it explores the real fashion trends in Qing dynasty, the culture connotation of fashion decoration in ancient China, the root and development of coat embroidery borders.</p>

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.935
Threshold uncertainty score0.281

Codex and Gemma teacher scores by category

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

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 head0.062
GPT teacher head0.294
Teacher spread0.233 · 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.

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

Citations1
Published2015
Admission routes1
Has abstractyes

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