Pemberdayaan Usaha Kecil Menengah (UKM)/Usaha Rumah Tangga (URT) Kerajinan Kulit di Kabupaten Bantul Yogyakarta
Bibliographic record
Abstract
Growth of Informal Sector UKM/URT leather so far has been getting the attention of the government , but not enough attention is because it has not touched the substance of empowering UKM/URT as part of the global economic system. This is because coordination, focus and formulation of each department tends to rule out a profitable strategy UKM/URT, but more nuanced political or business-oriented on the other side. Growth of UKM/URT themselves usually stop at the base phase where after working through internships (replication) for a bold new step on their own (work Independently) goes directly compete and survive. This method is very common UKM/URT for this so that UKM/URT less have a comparative advantage, because it is still a single fighter for all matters both for the production, management, marketing, etc. In fact, everything is done the traditional (manual, non-corporated). Under these conditions, the role of government and business associations are expected to be suporting system is vital for UKM/URT. Thus, in the era of regional autonomy of local governments should empower UKM/URT as the main pillars of the regional economy. The role of business associations are not limited to the expected orientation solely capital adequacy but also to think of innovation, improvement of production systems, design, quality control, management, marketing systems, as well as having a dual role that regulate the production and marketing systems, including the progressively explore marketing. Until this approach is necessary as a form of cultural and structural dynamics of society from an agrarian society to a modern society that direction must inevitably be faced by society as a whole is not denied even occur in all sectors of development.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.215 | 0.035 |
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".