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Record W3203224592 · doi:10.1177/2277436x211044050

The Detrimental Dialogue Between Indian Women, Beauty Discourse, Patriarchy and Indian Feminism

2021· article· en· W3203224592 on OpenAlexaff
Lydia VK Pandian

Bibliographic record

VenueJournal of the Anthropological Survey of India · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicMedia, Gender, and Advertising
Canadian institutionsMcMaster University
Fundersnot available
KeywordsBeautyPatriarchyIdeologyHegemonyGender studiesContext (archaeology)FeminismPower (physics)SociologyAestheticsHabitusTone (literature)HistoryPolitical scienceArtLiteraturePoliticsSocial scienceLaw

Abstract

fetched live from OpenAlex

This framework article analyses the established connection of body image and skin tone to the ideology of power and status and the need for Indian women to achieve those beauty standards to be celebrated in their field. Even though women have gained more power, they are still defined by and in the context of men in India. Men have subtly and constructively translated this power discourse over women that has been stretching across centuries through the channels of art, literature and the portrayal of the goddesses. This pressure to continually conform to beauty’s cultural ideals and sculpt oneself to those unattainable standards leads to body dissatisfaction. It affects the image the woman has of herself. The patriarchal structure that dominates the Indian women habitus has translated the ideology of this Western concept of beauty into a ‘common sense’ that has compelled women to impose a ‘self-hegemonic’ stance and the role of Indian feminism in fighting this emerging oppressive structure.

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)0.003
metaresearch head score (Gemma)0.002
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 score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0150.043
Scholarly communication0.0140.004
Open science0.0010.007
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.059
GPT teacher head0.372
Teacher spread0.314 · 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
Published2021
Admission routes1
Has abstractyes

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