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Record W2145544387 · doi:10.24036/jh.v11i1.623

NILAI-NILAI MORAL YANG TERDAPAT DALAM KABA PADA KESENIAN RABAB (Studi pada Sebuah Pertunjukan Kesenian Rabab di Nagari Duku Kecamatan Koto XI Tarusan Kabupaten Pesisir Selatan Sumatera Barat)

2012· article· en· W2145544387 on OpenAlexaff
Yesi Anita, Nurman Nurman, Aldri Frinaldi

Bibliographic record

VenueHumanus · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicCultural and Artistic Studies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsNonprobability samplingHumanitiesSociologyArtDemography

Abstract

fetched live from OpenAlex

This research aims to reveal religious and moral values in kaba (a type of Saga in Minangkabau literature) and rabab Pasisie (a type of percussion in Minangkabau particularly the one from Pesisir Selatan regency). The research is qualitative descriptive. The data, primary and secondary, is collected by observation, interview, and documentation. The interviewees are selected through purposive sampling. The data is then tested by triangulation of the sources, and then analysed using selection, reduction, classification, and presentation of data, which is later concluded. The result shows that rabab Pasisie is still fancied by the communities in Nagari Duku Kecamatan Koto XI of Tarusan District. The research concludes that kaba and rabab Pasisie embodies moral values that can be applied in the daily life of the community. We suggest that the leader of Nagari Duku Kecamatan Koto XI of Tarusan District promulgate the traditional rabab as a consideration to make it cultural tourism, while the Minangkabau society can implement moral values in kaba, and it is important that the district’s youth continue to learn and play rabab to maintain the traditional arts. Key words: Minangkabau kaba, rabab Pasisie, moral values, arts

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.023

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 studies0.0050.003
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.063
GPT teacher head0.297
Teacher spread0.235 · 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 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
Published2012
Admission routes1
Has abstractyes

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