DISORGANISASI PENERAPAN PSBB DI DKI JAKARTA SEBAGAI REFLEKSI KOMPLEKSITAS RELASI PEMERINTAH PROVINSI DKI JAKARTA DAN PEMERINTAH PUSAT
Bibliographic record
Abstract
Large-scale social restrictions or PSBB have brought up immense multidimensional effects within the Indonesian political landscape. One of the things which could be dissected from this regard would be in the governance system. In this sense, one might take a look at the current management of the COVID-19 pandemic within the Province of Special Capital Region of Jakarta. In this province, the Indonesian central government has often „collided‟ with the province‟s regional government; which ranging from issues such as social assistance, transportation, economic, and also law enforcement. The impact of such „skirmish‟ has taken its toll on all of the city‟s residents; but most importantly hit it the hardest for the city‟s poorest and most vulnerable group. With this in mind, the goal of this paper is to broaden the knowledge within the issue of pandemic management, especially within the Indonesian context. Besides, it also strives to find out several recommendations which should be taken by the government in order to „solve‟ this issue as comprehensively as possible.
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 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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".