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Record W2801682490 · doi:10.1080/13688790.2018.1461174

<i>The Little Nyonya</i> and Singapore’s national self: reflections on aesthetics, ethnicity and postcolonial state formation

2018· article· en· W2801682490 on OpenAlexaff
Jean Michel Montsion, Ajay Parasram

Bibliographic record

VenuePostcolonial Studies · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicSocioeconomic Development in Asia
Canadian institutionsDalhousie UniversityYork University
Fundersnot available
KeywordsPrideState (computer science)Ethnic groupNational identityIndigenousIdentity (music)SociologyGender studiesAestheticsAppealNegotiationNationalismHistoryAnthropologyPolitical scienceSocial sciencePoliticsLawArt

Abstract

fetched live from OpenAlex

Singapore’s postcolonial state formation process has combined the appeal/distress of a multiracial society with the nationalistic pride of economic development. In recent years, the city-state has witnessed a revival of Peranakan culture and history, referring to the descendants of early Chinese immigrants who integrated into Indigenous societies before becoming prized mediators for British colonisers in the nineteenth and twentieth centuries. We question how these references are strategically deployed as part of the process of postcolonial state formation and how their aesthetic representations support public discussions and debates about what defines contemporary (Chinese) Singaporean identity. By examining Peranakan representations in the television series The Little Nyonya from a Deleuzian perspective, it will be argued that Peranakan history and culture are mobilised to de-territorialise previous meanings of national ethnic markers, specifically Chineseness, and to re-territorialise a local sense of Indigeneity. In reaction to concerns over Mainlander identity, representations of Peranakan culture and history in The Little Nyonya support the indigenisation of a specific Chinese identity that is accessible to all Singaporeans, offering an aesthetic framework in which the ongoing process of negotiating between Singapore’s national self and other unfolds.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.015
Scholarly communication0.0050.003
Open science0.0000.003
Research integrity0.0010.002
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 head0.059
GPT teacher head0.387
Teacher spread0.327 · 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 designNot applicable
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

Citations11
Published2018
Admission routes1
Has abstractyes

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