Policing the COVID-19 pandemic: Police and public perceptions of enforcement of health protocols in the Fiji Islands
Bibliographic record
Abstract
The COVID-19 pandemic has become a global health security concern (World Health Organization, 2020), and governments have called upon police agencies to assist control the spread of the COVID-19 virus. This study looks at the new roles performed by police agencies in the context of the Fiji Islands. This study addresses two main research questions. Firstly, what are the issues and challenges faced by police officers when carrying out their COVID-19 duties? Secondly, what is the public perceptions of police officers’ effectiveness in enforcing COVID-19 health protocols? This study has utilized a mixed-method approach based on qualitative interviews with police officers and a quantitative survey of the public. The police officers' interviews reveal that police performed new health duties and ground-level police faced several challenges. The public survey findings reveal that most people were happy with police performance. We conclude by discussing the policy implications of our findings on police practice and the agenda for future comparative research in small island countries so that SIDs can learn from each other.
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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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".