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Record W2468177373 · doi:10.5539/ass.v12n7p42

Emergence of Chinese Han Retro Wedding Dress

2016· article· en· W2468177373 on OpenAlexvenueno aff
Li Niu, Tingting Xia, Rongrong Cui, Jie Lu

Bibliographic record

VenueAsian Social Science · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicFashion and Cultural Textiles
Canadian institutionsnot available
FundersSocial Science Foundation of Jiangsu Province
KeywordsStyle (visual arts)ChinaConsciousnessContext (archaeology)Chinese culturePromotion (chess)CommercializationAestheticsSociologyArtHistoryPolitical scienceLiteraturePsychologyLawPolitics

Abstract

fetched live from OpenAlex

Social changes led to the gradual disappearance of traditional Han costume. While in the context of national cultural revival, the "Chinese Hanfu movement" has given rise to the appearance and commercialization of Han Retro Wedding Dress, which including "Zhou style", "Han style", "Tang style", "Song Style" and "Ming style." Chinese history and culture, social democratic environment, economical market promotion and diverse aesthetic needs give the soil for these dresses. While contemporary wedding dresses in China are mostly westernized, and these retro dresses bring certain "reverse cultural shock" to Chinese marriage custom. The key of dealing with the "reverse cultural shock" and reviving Chinese costume culture should be following the market rules with sufficient cultural consciousness of the whole Chinese nation.

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)0.000
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: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.027
GPT teacher head0.278
Teacher spread0.251 · 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

Citations1
Published2016
Admission routes1
Has abstractyes

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