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Record W4404193878 · doi:10.1080/08865655.2024.2424822

“Cultural In-Betweenness” in Borderland Films of Malaysian and Indonesian Cinemas

2024· article· en· W4404193878 on OpenAlexvenueno aff
Mohd Erman Maharam

Bibliographic record

VenueJournal of Borderlands Studies · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicAsian Studies and History
Canadian institutionsnot available
Fundersnot available
KeywordsIndonesianMovie theaterBetweenness centralitySociologyPolitical scienceAestheticsEconomic geographyMedia studiesHistoryGeographyPhilosophyLinguisticsArt historyMathematicsStatistics

Abstract

fetched live from OpenAlex

This paper examines cinematic representations of the borderlands between Malaysia-Thailand and Malaysia-Indonesia in the twenty-first century. The films focusing on the region explore problematic issues such as the intersection of traditions, issues of identity and belonging, the modern nation-state system, and the citizens in these peripheral areas. This paper employs film discourse analysis, and the ideas discussed herein are crucial to the national cinemas of the region, as they operate in a manner akin to Deleuze and Guattari’s concepts of the war machine, the smooth space, and nomadology. These representations raise questions about uneven power dynamics between the hegemonic center and the peripheral other. This investigation analyses two films: Batas (Rudi Soedjarwo, 2011) from Indonesia and Bunohan: Return to Murder (Dain Said, 2012) from Malaysia. This paper argues that the portrayal of borderlands and borders challenges the stability of inwardly focused and ethnocentric national cultural identities by presenting the borderlands of this island region as nomadic spaces, conveying a nomadic ethos and a sense of “in-betweenness” among its people.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.314
Threshold uncertainty score0.577

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.027
GPT teacher head0.341
Teacher spread0.314 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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