机构地区:[1]西北大学城市与环境学院,西安710127 [2]西北大学陕西省地表系统与环境承载力重点实验室,西安710127
出 处:《热带地理》2022年第9期1500-1512,共13页Tropical Geography
基 金:国家自然科学基金项目(42271239、41871144);西北大学“人地关系与空间安全”特色优势团队建设项目(2019)。
摘 要:基于“中国裁判文书网”获取的2008―2022年跨国拐入安徽省的拐卖妇女犯罪案例数据,综合运用空间分析等方法,分析安徽省跨国拐卖妇女犯罪的群体特征、时空分异和形成机制。结果表明:1)群体特征差异显著,其中作案人以31~50岁的青壮年男性为主,文化水平较低,且以汉族、苗族居多;被害人主要来自越南,且以介绍工作赚钱为由被拐骗为主,案发后多被遣返原籍或自愿留下;收买人主要为适婚年龄的单身男性及其父母,文化水平多为初中及以下。2)时间演变上,安徽省跨国拐卖妇女犯罪整体呈“峰”型变化趋势,经历波动低发—起伏增长—急速回落3个阶段,发生态势主要受人口政策、打拐力度、网站平台发展等因素的影响。3)空间分布上,拐出地主要为越、缅、柬、老4国和云南、广东、安徽等省份;中转省呈弧状分布,中转市“邻界”特征显著;拐入地集中在皖北和皖中,其中拐入市呈“南北平行双弧”向东辐射扩散,拐入县则呈皖北散状点型与皖南“抱团式”的差异空间格局,地理邻近选择倾向明显,且拐入县呈“单片―扩散―汇聚”的热点变化趋势;拐卖路径上,形成“越南―云南省文山州―马鞍山市含山县”和“柬埔寨―江西省景德镇市―合肥市庐江县”等主要路径,呈现“邻国拐出―边境/内陆中转―多地拐入”的“源―流―汇”路径通道。4)拐出地和拐入地之间的推拉效应为该类型犯罪的发生提供动力,促进作案人、被害人、收买人三方与拐出地、中转地、拐入地三地之间产生交互和耦合作用,促使犯罪路径的形成。The crime of transnational human trafficking significantly impacts social stability and state relations,and thus,deserves in-depth research from a geographical perspective.Based on 2008-2022 case data on the transnational trafficking of women in Anhui Province,obtained from"China Judgments Online,"this study uses statistical and spatial analysis methods to comprehensively explore group characteristics,spatial-temporal differentiation,and the formation mechanism of transnational women trafficking in Anhui.The results show that:(1)Tripartite-group characteristics are significantly different.The perpetrators are mainly young and middle-aged men,with a general education level of junior high school or below,mostly from the Han and Miao ethnic groups.Most victims are primarily from four countries-Vietnam,Myanmar,Cambodia,and Laos-with Vietnamese women making up the largest group.Victims are generally abducted into China voluntarily,on the pretext of finding a job to earn money.After the crime,most are repatriated to their home countries or stay voluntarily in the place of abduction.Most buyers are male farmers of marriageable age and their parents.(2)Transnational women trafficking in Anhui has followed a"peak"trend overall;It has evolved through three stages:low volatility in2003-2009,volatile growth in 2010-2017,and rapid decline in 2018-2020.This pattern has evidently been affected by China’s population policy,anti-trafficking efforts,and website-platform development.(3)Transit provinces are distributed in an arc,with the highest incidence in Yunnan,Jiangxi,and Anhui,in that order.Transit cities have a significant adjacent-boundary feature,with Wenshan,Jingdezhen,Honghe,and Lincang as the main points of contact.The destination cities show north-south parallel double arcs distribution pattern,radiating eastward,which radiate eastwards.The northern arc is dominated by Fuyang,Bozhou,and Suizhou,while the southern arc is dominated by Anqing,Hefei,and Maanshan.The destination counties are evidently characterized by geo
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