A Year of Covid-19: A Long Road to Recovery and Acceleration of Indonesia's Development
Why this work is in the frame
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Bibliographic record
Abstract
2020 is the year of Covid-19, Indonesia feels the enormity of this pandemic in various aspects of development. The Indonesian economy during the year slowed down to minus 5.3 percent in the second quarter of 2020 and in aggregate growth was minus 2.1 percent in 2020. The target of development planning in the National Medium Term Development Plan (Rencana Pembangunan Jangka Menengah/RPJMN) 2020-2024 was revised through the updating of the Government Work Plan (Rencana Kerja Pemerintah/RKP) in 2020, with the main priority of overcoming Covid-19. Then development began to be intensified in 2021 to pursue national priority targets that were abandoned due to Covid-19. The 2020 State Budget allocates around IDR 937.42 trillion for the prevention of Covid-19, including the accumulated APBD (Regional Revenue and Expenditure Budget) IDR 86.32 trillion, which makes the deficit financing for that year reach IDR 1,226.8 trillion. The Covid-19 pandemic control policy through Large-Scale Social Restrictions Policy (Pembatasan Sosial Berskala Besar/PSBB) has had ups and downs, especially when coupled with the new normal policy. The Policy for Limiting Micro Community Activities (Pemberlakuan Pembatasan Kegiatan Masyarakat/PPKM) as a substitute for PSBB was implemented in early February and the parallel national vaccination program is expected to support accelerated development as outlined in the RKP 2021. In 2021, the Covid-19 pandemic is still high in the world, and the acceleration of development proclaimed by the government gets a stretch of road that extends to be traversed.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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