ANALISIS DAMPAK PANDEMI COVID-19 TERHADAP KINERJA KEUANGAN DAERAH
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The COVID-19 pandemic is an outbreak of an infectious disease originating from the SARS-Cov-2 virus. As the virus grows, it causes various problems in various areas of life in society. The impact felt was so real with the cases of high death rates, unstable economy and other problems. The government, which has an obligation to make people's welfare take various policies to overcome this problem. From policy making, surely, it intersects with state finances which will ultimately affect the financial performance of the government itself. The purpose of this research is to determine the impact of the COVID-19 pandemic on the financial performance of local governments. The method used in writing this article is a qualitative method in the form of a literature review. The data obtained comes from secondary data, namely in the form of indirect retrieval via Google Scholar, Sinta and several articles that support the concept of the theme ranging from 2017-2022. The results of this study show that there have been changes in Indonesia's economic quarter and the regional budget experienced a minus number. Even so, the influence of the Covid-19 pandemic did not have a significant impact on the financial performance of local governments in several regions in Indonesia.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it