Regulation in the COVID-19 pandemic and post-pandemic times: day-watchman tackling the novel coronavirus
Bibliographic record
Abstract
Purpose While fighting with the novel coronavirus will not be the main goal of sectoral regulators, different regulatory authorities join the struggle by providing a regulatory response. The purpose of this paper is to address this regulatory response in pandemic gathered around eight thematic areas. Design/methodology/approach This paper discusses the regulatory response in pandemic gathered around eight thematic areas, namely, the objectives, rules and standards, authorization and permits, procedure, monitoring and surveillance, enforcement, accountability and an institution presenting regulatory actions to tackle coronavirus (COVID-19) in reference to day-watchman type regulation. Findings Tackling the COVID-19 pandemic should be a knowledge-based approach (taking as much as possible from best available practices with respect to the novel coronavirus) with a framework of rules, standards, authorization, permits and guidance, monitored and enforced in a way adjusted to conditions of the pandemic, being as safe (as non-physical, as online) as possible, with suspended or extended deadlines, free of unnecessary administrative burdens. In this way, regulation should be pragmatic and flexible, as under the day-watchman model. Research limitations/implications In a post-pandemic regime, in the short run, the regulators should try to minimize the social and economic challenges faced by consumers and entrepreneurs. Among them, one may find scaling back, at least temporarily, the rules developed in non-disaster contexts. However, in the end, the post-disaster reforms tended to strengthen regulators’ hands, also under the deregulated government. The day-watchman type regulation balances both, as a middle ground approach, being a bridge between “a total subordination” and “a complete release.” Practical implications The disaster management (including public law regulation) provided by public authorities when tackling the effects of hurricanes, earthquakes or tsunamis can be a benchmark for regulatory responses to the COVID-19 pandemic. This concerns the support offered to entities and individuals affected by the negative consequences of reducing or stopping their businesses and staying in isolation. Social implications The day-watchman approach, visible in certain examples of public response to COVID-19 may serve as a framework for establishing a regulatory regime that would automatically take effect in case of another pandemic, limiting delays in regulatory actions, reducing non-compliance and accelerating recovery. Originality/value This study provides an analysis of different theories on public regulation addressing the notion of regulation using the day-watchman theory, which could be applied in regulatory actions during a pandemic. The paper discusses concrete steps taken by regulatory authorities worldwide, bringing examples from the USA, Canada, the UK, France, China, Japan, Australia and New Zealand. It juxtaposes the regulatory experiences derived from different catastrophes such as hurricanes, earthquakes or tsunamis with the regulatory response in a pandemic.
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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 | 0.021 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.014 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".