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Record W4407741300 · doi:10.1386/safm_00091_1

Forbidden spectacles of a bygone era: An analysis of Malayalam cinema’s soft-porn noon-show culture

2024· article· en· W4407741300 on OpenAlexaff
Sony Jalarajan Raj, Adith K. Suresh

Bibliographic record

VenueStudies in South Asian Film & Media · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicSouth Asian Cinema and Culture
Canadian institutionsMacEwan University
Fundersnot available
KeywordsMalayalamNoonMovie theaterArtVisual artsComputer sciencePhysicsAstronomyArtificial intelligence

Abstract

fetched live from OpenAlex

The cultural paradigms of the soft-porn era in Malayalam cinema had an emancipatory quality where the sensationalized body of the ‘bombshell’ starlets captivated the voyeuristic perceptions of regional spectators. The celebration of these films by a suburban audience constructed a new public space for the realization of carnal desires and taboo fantasies. This article investigates how the soft-porn noon-shows contributed to a unique cultural experience of film-viewing in Kerala in the late 1990s that challenged the cultural elitism associated with regional cinema. It investigates the role of the audience in defining the historical significance of the noon-show theatres, together with their origin, popularity and fall in the larger narrative of the evolutionary metamorphosis of Malayalam cinema. The softcore phenomenon was an organic subversion of the hegemonic ideology of cinema, which has been used by upper-class cultural powers to maintain their moral presuppositions.

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)0.002
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: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.005
Scholarly communication0.0050.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.041
GPT teacher head0.291
Teacher spread0.250 · 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
Published2024
Admission routes1
Has abstractyes

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