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Record W2288510472 · doi:10.1111/sjtg.12143

Smell this: Singapore's curry day and visceral citizenship

2016· article· en· W2288510472 on OpenAlexaff
Jean Michel Montsion, Serene K. Tan

Bibliographic record

VenueSingapore Journal of Tropical Geography · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicSocioeconomic Development in Asia
Canadian institutionsCanadian Forces CollegeUniversity of TorontoYork University
Fundersnot available
KeywordsCitizenshipFraming (construction)CurryImmigrationNational identityPoliticsCognitive reframingEthnic groupGender studiesHarmony (color)Political scienceSociologyMedia studiesSocial psychologyGeographyPsychologyLawArt

Abstract

fetched live from OpenAlex

In August 2011, many Singaporean citizens grabbed their cooking pots and used the city‐state's national obsession with food to express growing dissatisfaction with immigration and integration trends. The ‘cook and share a pot of curry’ event—a local response to Chinese newcomers complaining about the smell of their Indian Singaporean neighbours’ food—is significant for its use of smell to catalyse a collective citizen reaction and for its reliance on contemporary social media. By analysing this event, we intend to (1) conceptualize the role of smell and viscera in framing citizenship; (2) understand how smells shed light on the city‐state's contemporary ethnic politics and sense of national identity; and (3) reframe the significance of curry day as an expression of visceral citizenship that complements how the state frames Singaporean citizenry. We maintain that curry day sheds light on a specific dimension of Singaporean citizenship, as it uses smell, viscera and embodied activism to mobilize against rationalistic state‐defined distinctions between local and international concerns, economic objectives and social cohesion, inter‐racial harmony and national identity.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.134
Threshold uncertainty score0.738

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0010.000

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 head0.017
GPT teacher head0.276
Teacher spread0.259 · 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 designObservational
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

Citations19
Published2016
Admission routes1
Has abstractyes

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