ADAPTASI DAN PERKEMBANGAN KESENIAN EBEG BANYUMASAN PADA KOMUNITAS DIASPORA JAWA DI SUMATRA SELATAN
Bibliographic record
Abstract
Kesenian Ebeg Banyumasan merupakan salah satu kesenian Jawa yang dibawa oleh kelompok diaspora Jawa di Desa Tegal Sari, Kecamatan Belitang 2, Kabupaten Oku Timur, Provinsi Sumatera Selatan. Penelitian ini bertujuan untuk menjelaskan upaya adaptasi dan perkembangan kesenian ebeg yang menjadikannya tetap diterima, tumbuh dan berkembang pada lingkungan sosial budaya yang baru. Metode yang diterapkan dalam penelitian ini terdiri dari tahap identifikasi masalah, tahap pengumpulan data, dan tahap analisis data beserta penarikan kesimpulan. Penelitian ini menghasilkan temuan berupa aspek kebertahanan kesenian ebeg yang tetap tumbuh secara dinamis karena adanya proses adaptasi dari sisi musikal dan pertunjukan (performance). Upaya inovasi dan pengembangan juga terus dilakukan dalam rangka beradaptasi dengan situasi dan kondisi pada lingkungan sosio-kultural di daerah transmigran, antara lain dalam hal penyesuaian bentuk, ruang, dan waktu pertunjukan terhadap konteks kebutuhan acara atau event, hingga pembauran ragam ekspresi seni dari para anggotanya yang beranekaragam (latar belakang sosial dan kultural) melalui wadah tradisi pergelaran kesenian ebeg. Seni dalam hal ini menjadi wadah interaksi budaya antar anggota masyarakat yang multi kultur dan multi etnis. \nKata kunci: Kesenian Ebeg, Diaspora Jawa, Adaptasi, Perkembangan, Interaksi Budaya
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".