KEPEMIMPINAN DAN KINERJA PIMPINAN PEREMPUAN
Bibliographic record
Abstract
This study aims to determine the performance of female village heads and lurah in carrying out their duties, to find out the perceptions of leaders, village staff, and the community of three villages and one kelurahan in Lombok Timur Regency about the performance of female village heads and lurah and to find out the challenges and obstacles. faced in carrying out their leadership. With the existence of gender equality, women currently do not only work in the domestic area, but many who work in the public area become leaders, such as those in three villages and one kelurahan in Lombok Timur Regency which are led by a woman. This research uses a qualitative method with a case study approach located in four villages in Lombok Timur Regency. The subjects of this research are village government staff, village heads/lurah, community, religious leaders, traditional leaders, and community leaders in three villages and one kelurahan in Lombok Timur Regency. The types of data and data sources are primary and secondary data. The data collection technique used the purposive sampling technique. Methods of data collection using observation, interviews, and documentation. Data analysis is data reduction, data presentation, and conclusion drawing. Test the validity of the data by deepening observations, in-depth interviews, and triangulation. The results of the research showed that the performance of the female village head was good, responsible discipline, and never procrastinating on her duties. And the distribution of development is continuously carried out following the programs that have been implemented. This was acknowledged by village staff and communities in three villages in Lombok Timur Regency. The community's perception of the performance of the female village head/lurah is that the performance of the female village head/lurah is quite good when compared to the performance of the male village head/lurah. Female village heads have high participation, often provide examples, and invite the community to work together and make the village they lead more advanced. The challenges and obstacles faced by female village heads are when taking care of their household. In addition to being a leader in her village, she is also a housewife who must be able to divide her time between household work and her official work.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".