Bibliographic record
Abstract
This study aims to determine the Village Fund Management in Togomangura Village. To achieve these objectives, qualitative research methods are used to decipher data descriptively. Data collection techniques are done by observation, interviews, and documents and archives using qualitative descriptive analysis techniques. The results showed: 1). For the stages of village financial planning in Togomangura Village, the Togomangura village government has managed the village fund finances in accordance with Permendagri Number 113 of 2014 concerning Village Fund Financial Management. 2). For the Village Fund budgeting phase in Togomangura Village, it has been carried out in accordance with existing principles, namely by budgeting village funds in accordance with the RKP of the Village that was determined at the planning stage and in accordance with Permendagri Number 113 of 2014 concerning Village Financial Management. 3). The implementation of Village Fund Financial Management in Togomangura Village has been very good and in accordance with applicable regulations namely Permendagri No. 113 of 2014 concerning the implementation of village finances and the PDTT Permendes Number 19 of 2017 concerning Priorities for the Use of Village Funds in 2018. 4). The administration of the Village Fund Financial Management Program in Togomangura Village is already good, because it is in accordance with applicable regulations namely Permendagri No. 113 of 2014 concerning the implementation of village finance. 5). Village Fund Financial Reporting in Togomangura Village is not in accordance with Permendagri No. 113 of 2014 concerning village financial management. This is evidenced by the late TPK Field and Village Treasurers in submitting reports. 6). Monitoring of Village Funds by the BPD, it can be concluded that the BPD in carrying out its functions runs well but is less than optimal. This is because there are several factors that create obstacles, namely Human Resources (HR) so that the awareness of BPD members is less than optimal in carrying out their duties and functions. 7). The use of Village Funds in Togomangura Village in 2018 is not in accordance with the priority of use according to the PDTT Regulation No. 19 of 2017 concerning the priority of using Village Funds in 2018. 8). Inhibiting factors in the management of the Village Fund in Togomangura Village, namely: Human Resources, Late Reporting, Internet Networks, Community Understanding, Poor Coordination.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 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".