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Record W4405263190 · doi:10.53555/sfs.v10i1.3226

Empowering Narratives: A Feminist Critique of Physicality, Identity, and Representation in the Hindi Film Mary Kom

2023· article· en· W4405263190 on OpenAlexvenueno aff

Bibliographic record

VenueJournal of Survey in Fisheries Sciences · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicSouth Asian Cinema and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsHindiNarrativeIdentity (music)Representation (politics)SociologyAestheticsCommunicationGender studiesLiteratureArtLinguisticsPhilosophyPolitical sciencePoliticsLaw

Abstract

fetched live from OpenAlex

This paper, Empowering Narratives: A Feminist Critique of Physicality, Identity, and Representation in the Hindi Film Mary Kom, examines the biographical drama through a feminist lens, emphasizing its portrayal of gender, regional identity, and physicality.The film highlights Mary Kom's journey as a boxer from Manipur, exploring her defiance of societal norms and regional stereotypes.By integrating perspectives from Physical Education and English Literature, this study investigates themes such as women's physical strength, the struggles of motherhood, and North Eastern identity within a patriarchal and culturally homogenized context.Using feminist theories like intersectionality and embodiment, the analysis critiques the film's depiction of female empowerment, maternal sacrifice, and commodification of identity in Bollywood.While Mary Kom challenges gender norms, it also reveals the systemic barriers female athletes face.This interdisciplinary critique contributes to discourses on representation in Indian cinema, advocating for authentic, inclusive narratives.

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)0.005
metaresearch head score (Gemma)0.006
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: none
Teacher disagreement score0.018
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0180.059
Scholarly communication0.0100.008
Open science0.0020.008
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0060.000

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 head0.224
GPT teacher head0.360
Teacher spread0.136 · 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
Published2023
Admission routes1
Has abstractno

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