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Record W4220831824 · doi:10.1177/23938617221076181

Clapping Along or Clapping Back: Of the Discourse of Hijra Community’s Resilient Happiness in Y-Film’s Hum <i>Hain Happy</i>

2022· article· en· W4220831824 on OpenAlexaff
Prerna Subramanian

Bibliographic record

VenueSociety and Culture in South Asia · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicSouth Asian Cinema and Culture
Canadian institutionsQueen's University
Fundersnot available
KeywordsHappinessHumSociologyStatus quoPsychological resilienceAestheticsLawSocial psychologyPsychologyPolitical scienceHistoryArtPerformance artArt history

Abstract

fetched live from OpenAlex

Eva Illouz, whilst discussing her text Manufacturing Happy Citizens in an interview, points out that happiness in a neoliberal economy has become a way to measure our self-worth especially as it is individualised. Being happy, thus, means to be able to strive despite the odds and yet be optimistic: to be happy in a neoliberal setup is to be resilient. Indeed, resilience means bouncing back and putting your best foot forward in the gravest of circumstances, showing strength when things are against you: to be happy despite the odds. Keeping this aspect of resilience in mind, this essay is interested in broaching a more specific question: what happens when a structurally marginalised group is called resilient—when value of the group is solely located in its capacity to bounce back and remain within and not resist status-quo? The structurally marginalised group I will be referring to is the hijra community in India and I will discuss the idea of happiness in a video produced by Y films, the youth division of one of India’s biggest film production houses: Yash Raj films. The music video produced in 2016 is named ‘Hum Hain Happy (We are happy)’, a Hindi rendition of Pharrell William’s famous song of the same name, features six hijra community members from the city of Mumbai. The essay here offers a ‘friendly critique’ of the video’s efforts towards mainstreaming trans inclusion in representational practices which romanticise the struggle of the marginalised by valorising resilience as an inspirational response to systemic inequality. My critique, thus, does not invalidate representational practices in total but calls for looking at the dominant logics through which such representation is rendered possible. In so doing, I look at how the video’s narrative serves to quell collective resistance by translating individual resilience within status quo as happiness. On one hand, the makers of the video see the oppressed as valuable and respectable only in term of their resilient happiness and relatedly, by pedestalising this resilience as inspirational, essentialise/naturalise systemic inequalities and conditions of struggle. Anything that deters from this pedestal then is naturally seen as a negative response and not aspirational/inspirational. The essay first contextualises the video in the contemporary conditions of transgender rights in India and then proceeds to analyse its content regarding the narrative of resilience which obscures the conditions of transgender struggles in India, while elevating their positive attitude as inspirational, effectively obscuring the realities and possibilities of righteous rage and resistance.

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)0.004
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: Empirical
Teacher disagreement score0.052
Threshold uncertainty score0.102

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0340.036
Scholarly communication0.0130.006
Open science0.0020.007
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0030.001

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 head0.027
GPT teacher head0.241
Teacher spread0.214 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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