Lessons from the Grey Area: A Closer Inspection of At-risk Gamblers

The study takes a closer look at at-risk gamblers, with the objective to see how they differ from no-risk gamblers. The data comes from a national gambling survey in 2002, and the age group is 15–74 years. The sample consists of 4188 current gamblers with no current gambling problems or pathology. The analysis includes cross-tabulations and a logistic regression. The results show that at-risk gamblers differed substantially from no-risk gamblers in terms of demographic characteristics, gambling behaviour and the presence of other assumed risk factors. Demographic segments with a higher risk of falling into the at-risk group are men, young people, divorced or single people, and non-western immigrants. Furthermore, gambling problems in the family, beginners luck and misconceptions about winning chances significantly increased the odds for at-risk gambling. The study concludes that at-risk gamblers deserve more attention from research, that their similarity with problem gamblers increases the likelihood that many of them will eventually develop a gambling problem, and that their tendency to be superstitious about winning chances might be exploited in preventive work.     

Gambling Behavior of Student-Athletes and a Student Cohort: What are the Odds?

This study investigated the prevalence of gambling, gambling related NCAA violations, and disordered gambling in student-athletes (n = 736) with a comparison cohort of students (n = 1,071) at four universities. Student-athletes reported similar rates of gambling frequency, use of a bookmaker, and disordered gambling as students. After accounting for demographic differences, student-athletes were less likely to engage in sports wagering than students. Several risk factors for disordered gambling were identified, including being male and reporting at least one parent with a history of gambling problems. These findings suggest that problems associated with gambling are a university-wide issue with student-athletes meriting additional attention because of implications for the integrity of intercollegiate sports. Improved prevention and intervention efforts for collegiate gambling are recommended.     

解苦以求安宁：韧性视角下老年人的临终生命质量探究

随着人口死亡模式的转变与老龄化进程的加快,老年人的临终生命质量已成为大众关注的社会问题。本研究参考“身心灵平衡”韧性整合模型构建分析框架,运用半结构式访谈法与实物分析法,深入探索影响老年人临终生命质量的风险性与保护性因素及其作用路径。研究指出,身体的衰弱与疾痛和心理的情绪困扰是老年临终生命质量的风险性因素,它们均会损害老年人原有的平衡状态,且身心二者的负面影响存在相互强化的作用;而内在的灵性能力和外在的社会支持作为保护性因素,能够帮助老年人增强死亡准备、重构生命状态。基于上述结论,研究从身心社灵四个维度重点讨论了社会工作介入老年安宁疗护的发展方向。     

明清两代的公罪与私罪制度

中国古代将官吏犯罪区分为公罪和私罪,其目的是为了维护吏治的清明。明清两代的律、例、令、会典等条文中就有对公罪和私罪的相应规定。本文从明清两代的公罪与私罪的基本概念、具体规定、实际运行和影响因素四个方面对这一制度进行深入分析,以期对之有更加全面的认识。     

浅议新时期学生创造性思维的培养

新时期教育的着力点在于培养学生的创造力,而创造力的核心是创造性思维。但是,我国的传统教育却在某种程度上阻碍了学生创造性思维的发展。因此,我们必须引导学生敢于质疑、大胆提问,激发他们的好奇心和求知欲,注重发散性思维的培养,使他们学会学习、学会思考、学会创造。     

基于SEM-AHP方法的核电厂定量人为因素评价研究

文章基于人为因素分析与分类系统,分析了115起核电厂执照运行事件报告(Licensed Operation Event Report, LOER),并对影响核电厂事件发生的人为因素进行分类,采用结构方程模型方法得出各影响因素的路径系数,两两比较得到层次分析模型的判断矩阵,进而确定各因素的权重。同时对核电厂人为因素的重要性做排序分析,找到核电厂运行过程中的安全管理薄弱环节,从而促进核电厂系统平稳运行。     

移动短视频用户体验影响因素及作用机理研究——基于抖音APP用户的调查

随着短视频行业发展进入下半场,如何提升和完善用户体验成为各短视频平台可持续发展的关键。以用户体验五要素模型为基础,构建移动短视频用户体验模型,运用结构方程方法对模型的适用性进行检验,深入挖掘移动短视频用户体验的主要影响因素,为企业和相关平台方优化用户体验、提高用户留存率提供参考。研究发现：视觉吸引力、界面设计、交互、内容、需求满足对用户体验具有显著的直接影响,且这五个变量通过中介变量情感感知间接影响用户体验。基于此,短视频平台在秉持内容制胜的同时还需丰富互动形式,以优秀的界面设计和深厚的情感,抓住用户眼球、引发用户共鸣、满足用户多元需求,以此构建健康的平台生态圈。     

长三角地区农民资金互助合作社运行满意度及影响因素分析 ——以泰州市苏陈资金互助合作社为例

农民资金互助合作社是目前准新型农村金融机构在长三角地区的典型代表。基于对江苏省泰州市苏陈资金互助合作社的实地调研,重点考察社员对样本农民资金互助合作社运行的满意度及影响因素。研究发现：样本社社员对于农民资金互助合作社的整体运行情况基本持肯定态度;社员的家庭总收入、政府对农民资金互助合作社的支持力度以及社员在农民资金互助合作社借用的互助金额度,是影响社员对于农民资金互助合作社满意度的主要因素;农民资金互助合作社融资业务的开展,对于社员的农业和二三产业经营均具有正向促进作用;农民资金互助合作社的互助金投放的覆盖面与农村信用合作社等传统农村正规金融机构形成了互补关系。在此基础上,提出了相关政策建议。     

对译入译出的文化思考

从理论上说中国人可以进行中译英,但事实表明对外译出并不成功。此外,什么人适合译出、译什么、以什么方式译出值得思考。因此,就目前情况看,中国应以译入为主,要成为真正意义上的翻译输出国尚需时日。     

Macro-Economic Factors in Credit Risk Calculations: Including Time-Varying Covariates in Mixture Cure Models

The prediction of the time of default in a credit risk setting via survival analysis needs to take a high censoring rate into account. This rate is because default does not occur for the majority of debtors. Mixture cure models allow the part of the loan population that is unsusceptible to default to be modeled, distinct from time of default for the susceptible population. In this article, we extend the mixture cure model to include time-varying covariates. We illustrate the method via simulations and by incorporating macro-economic factors as predictors for an actual bank dataset.