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Focus on the Transformation of Female Relationships - The Screen Portrayals from "Comet Woman" to "Miss Bird"

2025· article· W4415619059 on OpenAlexaff

Bibliographic record

VenueCommunications in Humanities Research · 2025
Typearticle
Language
FieldSocial Sciences
TopicGender and Women's Rights
Canadian institutionsMaple Leaf Foods
Fundersnot available
KeywordsPerceptionFocus (optics)Focus groupFoundation (evidence)Content analysisSocial changeDiscourse analysis

Abstract

fetched live from OpenAlex

This article aims to study the changes in the relationships between female characters in films from the 20th century to the present, reflecting the portrayal of women in different social conditions and under the lenses of different directors. The author analyze the factors of society, culture, and industry, looking at the big picture through small details. In the article, the authors compare the two films "Miss Bower" and "The Comet Princess", by using horizontal and vertical comparisons as well as analysis of the language of the shots, and employ text analysis and comparative analysis methods to conduct the research. The authors found that in the two films, the relationships between women changed from hostile and mutually harming to mutual support. This is also a progress in social culture and a necessary trend of historical development. In most current films, the trend can also be observed. From these two simple films, we can discover the progress, diversity, and the non-simple struggle between women in the perception of relationships among women by society and culture. This is also a foundation for the development of feminism, and more people understand that when women unite, it is a greater strength.

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)0.003
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 score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.004
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.443
GPT teacher head0.461
Teacher spread0.018 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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