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Record W7163725307

Studi Deskriptif Instrumen Kucapi Pakpak di Kabupaten Pakpak Bharat

2025· other· en· W7163725307 on OpenAlexaff
Aswin Boang Manalu

Bibliographic record

VenueDigital Repository Universitas Negeri Medan (Universitas Negeri Medan) · 2025
Typeother
Languageen
Field
Topic
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsPeriod (music)
DOInot available

Abstract

fetched live from OpenAlex

Tujuaan penelitian adalah: (1) Untuk mengetahui teknik yang digunakan bermain Kucapi Pakpak di Kabupaten Pakpak Bharat, (2) Untuk mengetahui estetika instrumen Kucapi Pakpak di Kabupaten Pakpak Bharat, (3)Untuk mengetahui peran permainan Kucapi Pakpak dalam melestarikan budaya dan tradisi masyarakat Kabupaten Pakpak Bharat. Teori yang digunakan dalam penelitian ini ialah teori teknik permainan,teknik dasar,teknik menganak-anaki, teknik membungabungai, teori teori estetika, serta teori pelestarian budaya. Sampel penelitian ini sebanyak 3 orang .yaitu pemain kucapi dan tokoh budaya di Kabupaten Pakpak Bharat. Metode penelitian yang digunakan adalah metode penelitian kualitatif dengan jenis deskriptif kualitatif. Teknik pengumpulan data yang digunakan ovservasi,wawancar, dokumentasi. Hasil penelitian menunjukkan : (1) Teknik pyang digunakan dalam penelitian ini ialah teknik dasar,teknik menganak-anaki, teknik membungabungai, (2) Estetika Instrumen kucapi Pakpak melambangkan susunan dan kedudukan dalam system kekerabatan Pakpak yang terdiri dari Kesukuten, Puang/ Kula-kula, Dengan Sebeltek, dan Berru. (3) peran permainan kucapi di masyarakat berperan dalam melestarikan budaya, karena kucapi ini memiliki fungsi sebagai ekpresi pengungkapan emosional, penghayatan estetis, upacara agama, perlambangan sosial politik.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.267
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0040.005
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0060.004
Science and technology studies0.0020.002
Scholarly communication0.0010.005
Open science0.0050.004
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0070.006

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 head0.007
GPT teacher head0.201
Teacher spread0.194 · 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 designNot applicable
Domainnot available
GenreOther

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

Explore more

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