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Record W4413806713 · doi:10.54254/2753-7102/2025.26428

Unity in diversity: the religious, political, and cultural faces of Pancasila

2025· article· en· W4413806713 on OpenAlexaff
C. H. ZHANG

Bibliographic record

VenueAdvances in Social Behavior Research · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicAsian Studies and History
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsIdeologyPoliticsSociologySolidarityDemocracyUnity in diversityState (computer science)IndonesianPolitical economyPolitical scienceLawPhilosophy

Abstract

fetched live from OpenAlex

Pancasila, the five core principles proclaimed at the founding of the modern Indonesian nation-state, has served as a unifying concept and the bedrock of Indonesians shared nationhood. This paper traces the evolution of Pancasila as the enduring state ideology from its consolidation during the Soekarno era and sweeping expansion under the New Order regime to its decline and subsequent revival during and after the democratic transition. I argue that Pancasila is central to Indonesias unity in diversity. It emerged as what scholars aptly describe as an empty signifier, an inclusive and all-encompassing ideological vehicle that leaves room for diverse and often competing interpretations. This interpretive flexibility allows religious, political, and cultural groups within Indonesian society to pursue distinct goals under the banner of Pancasila without deviating from or undermining the states ideological unity. It facilitates the formation of imagined communities, through which divergent views and interests are represented, reconciled, and legitimized by the Pancasila state. The imagination is both singular and plural: while groups such as secular nationalists, conservative Muslims, New Order elites, democrats, and Javanists build solidarity within their respective, self-contained communities, they collectively submit to and willingly adhere to a unified and sovereign Indonesian nationhood in which different voices are acknowledged and accommodated.

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 categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.524
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.004
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 head0.114
GPT teacher head0.503
Teacher spread0.389 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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