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Female Characters in Contemporary Chinese Cinema: Case Studies of Modern Animated Films From 2015 to 2021

2025· article· W4417021142 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCommunications in Humanities Research · 2025
Typearticle
Language
FieldSocial Sciences
TopicMedia, Gender, and Advertising
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCharacter (mathematics)Style (visual arts)NarrativeHEROArgumentativeWhite (mutation)Japanese literature

Abstract

fetched live from OpenAlex

From 2015 to 2021, the feminist movement flourished, and gender studies emerged as a new discipline. This paper uses argumentative and literature analysis to conduct a detailed analysis of the portrayal of female characters in Chinese animated films, summarizing ways to improve the genre and techniques for creating excellent female characters. Among five representative domestic animated films selected, the number of female characters has significantly increased, from the absence of a female protagonist in Monkey King: Hero Is Back to the independent, strong, and courageous dual female protagonists in White Snake 2: The Tribulation of the Green Snake, with increasingly rich character designs. However, most contemporary Chinese film and television works still adhere to traditional gender stereotypes and suffer from many problems: for example, animated works featuring female protagonists often have simple themes, lack diverse character development, and exhibit bias in the portrayal and narrative style of strong women etc. Female characters should be portrayed as "people," not merely "female characters."

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.

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)0.005
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.098
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0020.003
Scholarly communication0.0000.001
Open science0.0020.003
Research integrity0.0000.001
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 head0.508
GPT teacher head0.552
Teacher spread0.044 · 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