Redai dili (Sep 2022)
Spatial and Temporal Patterns, Influencing Factors, and Prevention and Control Measures of Human Trafficking in Southwest China
Abstract
The crime of trafficking has a long history of causing serious harm to the victims, their families, and social stability, which has aroused widespread concern from the public and academic circles. Studies have shown that the southwest region of China has the highest incidence of trafficking crimes; thus, this study examines the trial data of Chinese judgment documents of the southwestern regions (Yunnan, Guizhou, Sichuan, and Chongqing) from 2008 to 2020. The study comprehensively uses text analysis, mathematical statistics, spatial analysis, and negative binomial regression test to explore spatial and temporal variation patterns and the factors influencing them. The study then proposes countermeasures for prevention, control, and management. The research shows that: (1) The overall high incidence of trafficking crimes occurred in the period 2009-2014, showing a wavy pattern of "three peaks and two valleys." The "three peaks" occurred in 2009, 2012, and 2014, whereas the "two valleys" occurred in 2010 and 2013. The highest incidence was in December, with the next highest incidences concentrated in May, June, July, and September for women, and May, July, August and September for children. On the whole, trafficking crimes occurred mostly in the summer months. The four provinces have had different degrees of inter-year and inter-month variations in the trafficking of women and children. (2) The overall spatial distribution is in the shape of a significant "southeast-northwest" axis, which is highly consistent with the boundary line between Sichuan and Chongqing, Yunnan, and Guizhou, and the inter-provincial border area is a hotspot for trafficking crimes. The provincial spatial distribution is the highest in Yunnan Province and the lowest in Chongqing. Trafficking mostly occurs at medical care institutions, stations, and rural residences with a large flow of people. (3) Negative binomial regression analysis of the random effects panel shows the incidence of trafficking crimes as influenced by the gender ratio of the population and the number of urban and rural residents' minimum living standards, while the per capita disposable income of rural residents, the registered urban unemployment rate, the child dependency ratio,and the volume of passenger transport have negative effects; whereas the population sex ratio, passenger traffic, and the number of urban and rural residents on the minimum subsistence allowance have a greater impact on the crime of trafficking of women. Finally, based on the analysis of the influencing factors, the three aspects of strengthening social construction, innovating prevention mechanisms, and strengthening combating mechanisms are proposed as the prevention and control countermeasures, with a view to dismantle the breeding ground for the crime of trafficking of women and children.
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