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Record W2884948531 · doi:10.1163/15685268-00192p01

The Pictorial Portrayal of Women and Didactic Messages in the Han and Six Dynasties

2017· article· en· W2884948531 on OpenAlexaff
Wen-chien Cheng

Bibliographic record

VenueNAN Nü · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicChinese history and philosophy
Canadian institutionsRoyal Ontario Museum
Fundersnot available
KeywordsEliteLienContext (archaeology)ArtHistoryIdeal (ethics)LiteratureVisual artsLawArchaeologyPolitical science

Abstract

fetched live from OpenAlex

This study examines the visual forms into which Liu Xiang’s (ca. 79-8 BCE) compilation Lienü zhuan (Categorized biographies of women) were translated during the Han (221 BCE-220 CE) and Six Dynasties (220-589) periods. After Liu Xiang’s work appeared, the images of lienü were established as a distinctive visual category, developed within a broader context of a didactic pictorial genre that engaged the use of images for both the living and the dead. They not only provided admonitory functions, but also were considered auspicious and visually pleasant. In addition to a body of excavated lienü images from these periods, I examine two later scrolls originally rooted in this pictorial genre of lienü, the Lienü renzhi tu (Sympathetic and wise women scroll) in the Palace Museum, Beijing, and the Nüshi zhen tu (Admonitions of the court instructress) in the British Museum. I argue that the two paintings epitomize an ideal female exemplar who is virtuous, graceful, and physically attractive – all these qualities and their textual associations served as markers of the owner/viewer’s elite status.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.004
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.020
GPT teacher head0.296
Teacher spread0.276 · 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 designNot applicable
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

Citations2
Published2017
Admission routes1
Has abstractyes

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