EDUKASI MANAJEMEN BISNIS GUNA MENGOPTIMALKAN PENGELOLAAN BUMDES DI KECAMATAN BRANG ENE KABUPATEN SUMBAWA BARAT
Bibliographic record
Abstract
This activity was carried out by the Brang Ene District Government, West Sumbawa Regency and in collaboration with Bumigora University Lecturers. The activity was conducted on August 27 2023 and involved BUMDes representatives from all villages in Brang Ene District. The stages of implementing this activity consist of 4 implementation steps, namely: Provide information, Reinforce with exercises, Review information, Verify knowledge. Previously, the Team identified that BUMDes management in Brang Ene District was not managing resources and achieving business goals effectively. After implementing education regarding business management, it was found that there was an increase in people's understanding and skills in terms of business management. This activity still requires ongoing support from local governments, educational institutions and other related parties to ensure the success and sustainability of this educational program in optimizing BUMDes management in the region.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.028 | 0.004 |
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".