Implementasi Platform Si Cantik Bangsa di Kabupaten Kebumen dalam Pembangunan Desa
Bibliographic record
Abstract
Si Cantik Bangsa is a platform that aims to record participation and equality in village development. Through this community service, the focus is emphasized on understanding the problems of women's empowerment in development in three villages, namely Logede Village, Ampelsari Village, and Kaliputih Village in Kebumen Regency. In this context, the main concern is overcoming the significant decline in the Gender Empowerment Index which is a serious challenge faced by the Community and Village Empowerment Service (PMD). In an effort to overcome this problem, the PMD Department introduced an innovative program known as Planning Literacy Women (WANI LEmPER) which is in line with the Sustainable Development goals (SDGs) related to gender equality and women's empowerment. However, even though the WANI LEmPER program has been implemented, there are still obstacles that arise due to cultural resistance and rejection from various parties. Therefore, this service offers a solution through the implementation of Si Cantik Bangsa, an information technology-based platform that aims to document the activities of LEmPER WANI cadres and monitor women's participation. The service results show that indicators of success have been achieved, where 65% of respondents understand the benefits and features of Si Cantik Bangsa, while 25% still do not understand them. Thus, the use of this platform is considered a strategic step in increasing women's empowerment in village development planning to achieve SDGs and Gender Empowerment goals.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.054 | 0.008 |
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".