Evidence map›Paper›PMID 39149048›Full record

ArticleHeliyon2024

Scientific uncertainty and the challenges of applying criminal law: Lessons from China's COVID-19 response.

Yong Ma, Xiaolin Zhang

Abstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Yong MaSchool of Management, Shandong Second Medical University, No. 7166 Baotong West Street, Weifang, Shandong, 261053, China.
Xiaolin ZhangSchool of Management, Shandong Second Medical University, No. 7166 Baotong West Street, Weifang, Shandong, 261053, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study addresses the complexities of applying criminal law during public health emergencies, particularly under the shadow of scientific uncertainty, and explores the challenge of balancing public health protection with individual rights. The primary aim is to dissect the application of criminal law in the context of the COVID-19 pandemic in China, focusing on the impact of scientific uncertainty on legal decision-making and the efficacy of criminal law interventions in public health crises. This study utilized a doctrinal method combined with case studies, integrating theoretical frameworks on risk and uncertainty with an analysis of China's legal responses to COVID-19. It involved assessing legislative and policy documents alongside judicial decisions, focusing on their alignment with evolving scientific understanding and public health strategies. The study reveals significant hurdles, including the limitations of empirical rules in judicial judgments, the emergence of technocratic bureaucracy, and the complexities surrounding risk mitigation and legal attribution under uncertain conditions. It highlights the inadequacy of traditional criminal law mechanisms to respond dynamically to the evolving landscape of public health emergencies. To address these challenges, the study recommends the development of temporary criminal legislation tailored to public health emergencies, the adoption of risk-based criminal law approaches, and the refinement of individualized risk assessment procedures. These measures aim to provide a more flexible and effective legal framework capable of safeguarding public health while ensuring the protection of individual liberties during crises.

Indexed as

ChinaCOVID-19Implementation of criminal lawPublic health emergencyRisk assessmentRisk criminal law

Identifiers

PMID39149048
PMCPMC11325063

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.