MétaCan
Menu
Back to cohort
Record W2911555578 · doi:10.5539/ass.v15n2p172

An Art Phenomenon Under the State Control: Case Study on Shadow Puppet Performance

2019· article· en· W2911555578 on OpenAlexvenueno aff
Sutiyono Sutiyono

Bibliographic record

VenueAsian Social Science · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicEducation, Sociology, Communication Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHegemonyObedienceShadow (psychology)State (computer science)PoliticsRuling classGovernment (linguistics)PhenomenonSociologyPower (physics)Order (exchange)Class consciousnessLawConsciousnessPolitical scienceLaw and economicsEpistemologyPsychologyEconomicsPsychoanalysisComputer sciencePhilosophy

Abstract

fetched live from OpenAlex

This article aimed at revealing the ruling class and the group being ruled in the society. The concern on the ruling party is to create obedience and to eliminate resistance from the ruled group. In this case, Gramsci presented the theory of hegemony by taking control on intellectually and morally leadership that can be accepted through consciousness process. In line with the explanation of hegemony, it seems that the Indonesia government, in the era of New Order (Orde Baru) from 1966 till 1998, was a powerful state with the highest authority control and became a determining force against the socio-political dynamics in the society. During Nee Order period, the state was truly capable of leading and dominating the field of power in various fields of development and statehood. One way to build hegemony is through institutions that determine the cognitive structure in the society, one of them was through the art of puppet. Consequently, puppeter (dalang) as one of intellectual figures in the society was controlled in order to socialize Golkar Party, as the political instrument. It can be concluded that the New Order government has successfully hegemoned the art of puppet.

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)0.005
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.227
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0050.003
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.068
GPT teacher head0.420
Teacher spread0.351 · 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 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

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueAsian Social ScienceSame topicEducation, Sociology, Communication StudiesFrench-language works237,207