From Movement Control to National Recovery Plan: Malaysia’s Strategy to Live with COVID-19
Bibliographic record
Abstract
With COVID-19 vaccination gaining momentum, strict lockdowns have been perceived as no longer necessary due to their far-reaching socioeconomic impacts. This overview aims to provide insight into Malaysia’s strategy in preparing to live with COVID-19 through stage-wise transition. This overview examined scholarly articles, news articles as well as official government announcements and data pertaining to the National Recovery Plan (NRP) which replaces COVID-19 lockdowns officially known as Movement Control Order (MCO) in Malaysia. NRP, which presents a stage-wise relaxation of lockdown leading ultimately to conditional reopening of all sectors and lifting of travel restrictions, adopts three major indicators for transitions of phases. The indicators are daily new COVID-19 cases, occupancy rate of intensive care units and full vaccination rate. Domestic travel initiatives have been initiated during the NRP, allowing domestic visits to certain tourist spots in the nation. Interstate travel in most parts of the nation has also been permitted without needing to show a negative COVID-19 test. On 28 October 2021, six states and three federal territories of Malaysia were already in phase 4 of NRP, which is the ultimate phase of lockdown relaxation, while all other states were in phase 3. This has resulted in a positive outlook on the gross domestic products of Malaysia in quarter 3, 2021. This overview highlights that a different approach to COVID-19 is necessary as total elimination of COVID-19 is not yet in sight. It sheds light into the use of pertinent indicators or indices to capture the status of COVID-19. Keywords: COVID-19; indicators; Malaysia; MCO; National Recovery Plan;Vaccination.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".