Digitalization of Precise Sentencing Recommendations for Mediate Bribery in View of Revealed Preference TheoryBased on Digital Analysis and Modeling of 293 Mediate Bribery Cases

Digitalization of justice has advanced precise sentencing recommendations among China’s procuratorates. However, judicial activities might be affected by the revealed preferences of judicial officers, making them not directly fit technical algorithms. The structured analysis of 293 cases of judgment exposed difficulties about the digitalization of sentencing recommendations for mediated bribery. Specifically, this special form of crime corresponds to multiple legal provisions, lacks prevailing sentencing rules when the amount is particularly large, and is closely related to social interpersonal relationships. Based on the revealed preference theory, judicial behavior can be integrated into the analysis and evaluation of sentencing activities, which helps to improve the digital analysis of sentencing recommendations and then build an algorithm model of declared sentence and fine punishment for such crimes. The model preliminarily reveals that when judicial officers apply the same sentencing consequences for different amounts involved, they may partially deviate from or even change their theoretical effect due to revealed group preferences.