The rationality of the punishment ladder: evidence from a quasi-natural experiment in China

As implementing a punishment ladder is an important way of establishing a balance between crime and punishment, the task of investigating the scientific and rational nature of the punishment ladder is highly significant. This paper explores the rationality of the punishment ladder employed in the context of the crime of infringing upon citizens’ personal information. Specifically, this research employs methods such as regression discontinuity design. The results reveal that after a judicial interpretation in 2017 defined the amount of information corresponding to different circumstances surrounding this crime, a significant discontinuity pertaining to fixed-term imprisonment sentences emerged at the threshold of the amount of information. This finding suggests the penalties associated with the different ladders of punishment used in this context are insufficiently connected, thus standing in contrast to the principle of a balance between crime and punishment. Furthermore, the larger the amount of information is, the lower the penalty per unit of information. This finding suggests that the threshold has a strong deterrent effect; however, once this threshold is crossed, the deterrent effect becomes sharply weaker, and no gradual deterrent ladder has yet been developed. Therefore, we suggest that the amount of information that corresponds to different circumstances of the crime should overlap with the aim of weakening the decisive role played by the threshold in this context. In addition, we recommend that larger quantities of information should be combined with more severe fines with the goal of ensuring that the purpose of punishment is achieved.

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Publication Details

Journal
Humanities and Social Sciences Communications
Published
2025-06-07
DOI
https://doi.org/10.1057/s41599-025-05073-7
Primary Topic
Law, Economics, and Judicial Systems
Type
article
Field-Weighted Citation Impact
0.00

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article

The rationality of the punishment ladder: evidence from a quasi-natural experiment in China

Ke Jiang, Fang Wang
Humanities and Social Sciences Communications
Law, Economics, and Judicial Systems
article

The rationality of the punishment ladder: evidence from a quasi-natural experiment in China

Ke Jiang, Fang Wang
article en

Abstract

As implementing a punishment ladder is an important way of establishing a balance between crime and punishment, the task of investigating the scientific and rational nature of the punishment ladder is highly significant. This paper explores the rationality of the punishment ladder employed in the context of the crime of infringing upon citizens’ personal information. Specifically, this research employs methods such as regression discontinuity design. The results reveal that after a judicial interpretation in 2017 defined the amount of information corresponding to different circumstances surrounding this crime, a significant discontinuity pertaining to fixed-term imprisonment sentences emerged at the threshold of the amount of information. This finding suggests the penalties associated with the different ladders of punishment used in this context are insufficiently connected, thus standing in contrast to the principle of a balance between crime and punishment. Furthermore, the larger the amount of information is, the lower the penalty per unit of information. This finding suggests that the threshold has a strong deterrent effect; however, once this threshold is crossed, the deterrent effect becomes sharply weaker, and no gradual deterrent ladder has yet been developed. Therefore, we suggest that the amount of information that corresponds to different circumstances of the crime should overlap with the aim of weakening the decisive role played by the threshold in this context. In addition, we recommend that larger quantities of information should be combined with more severe fines with the goal of ensuring that the purpose of punishment is achieved.

Humanities and Social Sciences CommunicationsVol. 12(1)
Shandong University (CN), Shandong Normal University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 81%
Law, Economics, and Judicial Systems
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