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Record W3196829712 · doi:10.1353/jeu.2021.0008

Young Banyumasan Street Traders as Shapeshifters of Modernity: Refreshment, Production, and the Pursuit of Pranks and Jokes in Jakarta

2021· article· en· W3196829712 on OpenAlexvenueno aff
Traci Marie Sudana

Bibliographic record

VenueJeunesse Young People Texts Cultures · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicAsian Studies and History
Canadian institutionsnot available
Fundersnot available
KeywordsSociologyTemporalitiesScholarshipAgency (philosophy)Shadow (psychology)ModernityEthnographyGender studiesAestheticsDomestic workWork (physics)Social sciencePsychologyPolitical scienceArtPsychoanalysisAnthropologyLaw

Abstract

fetched live from OpenAlex

Banyumasan Javanese people of Indonesia are often revered as funnier than other Javanese. Ethnographic accounts herein illuminate how young, Banyumasan street traders in Jakarta perform and participate in laughing, joking, and pranking at work. Intersectional analysis reveals the utility of joking and pranking as heuristics to understand the affective dimensions of status, stigmatization, migrating for work, and growing up in Indonesia. The polysemic nature of jokes and pranks reference camaraderie and othering, incongruities and expectations, agency and oppression, as well as intersubjective relations between young men at work. This view of Banyumasan street traders as urban jokers and jesters, producing and consuming humour "from below" for and about each other, departs from previous scholarship on humour in Java, which has focused on how clown characters in staged shadow puppet <i>(wayang kulit)</i> performances have asserted and perpetuated inequalities through a refined-unrefined <i>(halus-kasar)</i> binary whereby those deemed kasar are seen as lacking something. This article, in contrast, asserts the utility of jokes and pranks to refreshing and regenerating understandings of <i>kasar</i>, what it is to be human, and the temporalities, spatialities, and intersubjectivities of boys growing up and working in Indonesia's street economy.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.333
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.274
Teacher spread0.262 · 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 teacher head, 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

Citations1
Published2021
Admission routes1
Has abstractyes

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