Community-based policing to control COVID-19 outbreak at communal clusters: A Vietnam perspective
Bibliographic record
Abstract
The COVID-19 outbreak and its practical impacts are changing policing and police responses. Alongside the relentless efforts of the health sector, the role of police forces has been the subject of debate between the global South and North. As the first study in Vietnam, this paper explains how Vietnam’s police applied community-based policing to prevent and detect the interlaced occurrences among old and new patients at the communal cluster. Multiple sources were used to collect secondary data on police responses in the first lockdowns between February and March 2020. Online interviews with police leaders and six frontline officers were conducted to collect primary data. The findings show that, in each case, Vietnamese police implemented dynamic operations as much as possible in an effort to elicit voluntary collaborations to detect and contain COVID-19. Police used “onion-layer” and “door-to-door” approaches to coordinate and cooperate with their partners in the health sector. In addition, delivering persuasive propaganda was highly prioritized to incite local people to take up preventive measures rather than enforce them. The paper concludes with four specific recommendations and further discussions aimed at improving community-based policing’s effectiveness in future exceptional circumstances.
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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 | 0.015 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.009 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.005 |
| 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 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".