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Record W2118235249 · doi:10.1017/s0026749x06001831

‘Only Women can Change this World into Heaven’ Mei Niang, Male Chauvinist Society, and the Japanese Cultural Agenda in North China, 1939–1941

2006· article· en· W2118235249 on OpenAlexaff
Norman Smith

Bibliographic record

VenueModern Asian Studies · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicJapanese History and Culture
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsHeavenChinaEmpireColonialismHistoryAncient historyNovellaArtLiteratureArchaeology

Abstract

fetched live from OpenAlex

From 1939 to 1941, Mei Niang (b. 1920) penned three of her most famous novellas, Bang (Clam)(1939), Yu (Fish)(1941), and Xie (Crabs)(1941). Each of these works sheds light on the struggle of Chinese feminists in Japanese-occupied north China to realize ideals that stood in stark contrast to the conservative constructs of ‘good wives, wise mothers’ (xianqi liangmu) favoured by colonial officials. The contemporary appeal of Mei Niang's work is attested to by a catch-phrase, coined in 1942, that linked her with one of the most celebrated Chinese women writers of the twentieth century, Zhang Ailing (1920–1995): ‘the south has Zhang Ailing, the north has Mei Niang’ (Nan Ling, Bei Mei). Both women attained great fame in Japanese-occupied territories, only to have their achievements tempered by condemnation of the environments in which they forged their early careers. The Chinese civil war that followed the collapse of the Japanese empire propelled the two writers along divergent trajectories: Zhang Ailing moved to Hong Kong and the United States, where she achieved iconic status, while Mei Niang remained in the People's Republic of China, to be vilified. As one of the pre-eminent ‘writers of the enemy occupation’ (lunxian zuojia), Mei Niang was persecuted by a Maoist regime (1949–1976) dedicated to the refutation of the Japanese colonial order in its entirety.

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)0.001
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.150
Threshold uncertainty score0.299

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0170.013
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.029
GPT teacher head0.282
Teacher spread0.253 · 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

Citations3
Published2006
Admission routes1
Has abstractyes

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Same venueModern Asian StudiesSame topicJapanese History and CultureFrench-language works237,207