新冠肺炎疫情与全球安全文化的退化

安全文化是一个社群就怎样界定安全和安全威胁、怎样保障和实现安全所达成的主体间理解和共同知识。冷战之后,全球化推动了一个全球社会的初步形成,因之也催生了一种以开放安全、共同安全与合作安全为基本内容的合作型全球安全文化的雏形。但是由于全球治理失灵,不断出现且日益积累的全球性威胁得不到有效应对,民粹现实主义强势兴起,合作型全球安全文化屡遭重创,开始向以封闭安全、孤立安全、零和安全的冲突型安全文化转变,明显降低了国际安全合作的几率。抗击新冠肺炎疫情中的全球公共安全合作的失败就是一个明显的例证。虽然人类向共同体进化的历史大趋势不可阻挡,但在一段时间内,合作型全球安全文化与冲突型全球安全文化的激烈竞争将会是国际关系的新常态。     

Situational factors and police use of force across micro-time intervals: A video systematic social observation and panel regression analysis

The current study analyzes police use of force as a series of time-bound transactions between officers, civilians, and bystanders. The research begins with a systematic social observation of use-of-force events recorded on police body-worn cameras in Newark, New Jersey. Researchers measure the occurrence and time stamps for numerous participant physical and verbal behaviors. Data are converted into a longitudinal panel format measuring all observed behaviors in 5-second intervals. Panel logistic regression models estimate the effect of each behavior on use of force in immediate and subsequent temporal periods. Findings indicate certain variables influence use of force at a distinct point in time, whereas others exert influence on use of force across multiple time periods. The most influential variables relate to authority maintenance theoretical constructs. This finding supports prior perspectives arguing that police use of force largely results from officer attempts to maintain constant authority over civilians during face-to-face encounters. Nonetheless, a range of additional variables reflecting procedural justice, civilian resistance, and bystander presence significantly affect when police use force during civilian encounters. Results provide nuance to theoretical frameworks considering use of force as resulting from the interplay between officer and civilian actions and reactions.     

Medical examiner response to the drug overdose epidemic in King County Washington: “Real-time” surveillance,data science,and applied forensic epidemiology

As the overdose epidemic overwhelmed medicolegal death investigation offices and toxicology laboratories, the King County Medical Examiner's Office responded with “real-time” fatal overdose surveillance to expedite death certification and information dissemination through assembling a team including a dedicated medicolegal death investigator, an information coordinator, and student interns. In-house testing of blood, urine, and drug evidence from scenes was performed using equipment and supplies purchased for surveillance. Collaboration with state laboratories allowed validation. Applied forensic epidemiology accelerated data dissemination. From 2010 to 2022, the epidemic claimed 5815 lives in King County; the last 4 years accounted for 47% of those deaths. After initiating the surveillance project, in-house testing was performed on blood from 2836 decedents, urine from 2807, and 4238 drug evidence items from 1775 death scenes. Time to complete death certificates decreased from weeks to months to hours to days. Overdose-specific information was distributed weekly to a network of law enforcement and public health agencies. As the surveillance project tracked the epidemic, fentanyl and methamphetamine became dominant and were associated with other indicators of social deterioration. In 2022, fentanyl was involved in 68% of 1021 overdose deaths. Homeless deaths increased sixfold; in 2022, 67% of 311 homeless deaths were due to overdose; fentanyl was involved in 49% and methamphetamine in 44%. Homicides increased 250%; in 2021, methamphetamine was positive in 35% of 149 homicides. The results are relevant to the value of rapid surveillance, its impact on standard operations, selection of cases requiring autopsy, and collaboration with other agencies in overdose prevention.     

Beyond Dyads: Regional Democratic Strength’s Influence on Dyadic Conflict

Over the history of modern international relations research, we have moved from systemic and regional studies to empirical explorations of dyadic interactions. However, our statistical models have put the details of dyadic interactions under a microscope at the expense of ignoring the relevant regional context that these dyads interact in. This development has been in part due to computational limitations, but do we really believe that decision makers interact with one another while ignoring the regional power balance and the wishes of regional powers? In this article, I take a look at the well-researched relationship between democracy and peace by using a multilevel approach to dyadic interactions and the regions they are embedded in. The findings suggest that when the regional power balance favors democracies, it influences conflict between dyads, especially mixed dyads, by increasing the costs of aggression by autocracies and establishing regional norms of cooperation and compromise.     

In Search of Strategies to Face the Economic Crisis: Evidence from Greek Farms

This study examines the strategies – defensive or aggressive, individual or collective – undertaken by sheep farms in a Greek rural area in order to face the repercussions of the economic crisis and their effects on the productivity and economic performance of these farms. The article presents the results of a farm management survey conducted in 2010 and repeated in 2014 in northern Evros, Greece. The mix of strategies – mainly passive – adopted by farmers shows their confusion in the face of crisis conditions, which has resulted in reduced productivity, more use of family labour and a rise in collective actions.     

开放政府与修改《政府信息公开条例》的内容定位

修改《政府信息公开条例》要处理好《政府信息公开条例》与其他行政公开立法的分工,重大行政决策过程公开、行政执法公开等为行政行为中的公开机制,可在行政程序立法中予以规定。修法应当回归《政府信息公开条例》作为权利法的法律属性,实现知情权法定,确立公开原则,扩展公开范围,取消限制公民知情权实现的相关机制。修法还应回应互联网时代对开放政府数据提出的立法需求,完善政府数据开放的内部与外部机制。     

国际服务贸易之反倾销法律制度初探

反倾销法律制度是WTO所允许的国际货物贸易的有效保障措施。在贸易自由化浪潮下,国际服务贸易遭到不公平竞争的损害和威胁,并呈愈演愈烈之势。因此,在国际服务贸易保障措施缺位的情况下,探讨货物贸易的反倾销制度与服务贸易接合的可行性与必要性,并以GATS的相关规定为依据尝试对服务贸易的反倾销制度进行实体构建,具有重大的理论和现实意义。     

Firm entries and exits in Estonian urban municipalities: urban hinterlands and rural peripheries, 2005–2012

This paper studies firm entries and exits in Estonian urban areas, urban hinterlands, and rural peripheries following EU accession, and it analyzes the effects of changes in population density, employee income level, unemployment, and economic climate on firm entries and exits. It concludes that the firm entry rate exceeded the exit rate in all of the years between 2005 and 2012. The urban hinterland is characterized by the highest level of both entries and exits. The fixed-effect regression models show that income and recession, which are the most significant factors to impact on local entrepreneurship, have a similar effect on different municipality types.     

县域金融发展与产业集聚区经济增长——以浙江为例

本文以浙江为例,在经济增长理论的基础上,建立了县域金融发展与产业集聚区经济增长之间相互作用的内生模型,基于浙江省22县（市）的县级数据,运用面板数据模型对县域金融发展与产业集聚区经济增长的互动关系进行了实证检验,比较了各产业集聚区经济增长的影响因素。研究发现：浙江县域金融发展规模、固定资产投资、实际利用外资与产业集聚区经济增长存在高度正相关关系;金融发展效率对产业集聚区经济增长的检验效果不显著;实际利率对产业集聚区经济增长的影响不显著,提出在执行利率政策时,不能采用金融发展理论中提高利率、解除金融抑制的政策手段。     

A model for adoption of mobile banking services using classification and regression trees

The analysis and improvements of bank performance is a challenging issue for bank managers. Among various banking services, mobile banking is one of the most risky fields that is prone to customer resistance. Mobile banking is a form of banking transaction carried out via a mobile phone. Mobile banking allows bank customers to check their account balances and perform credit card transaction, as well as provide information on the latest transaction made by customers. This paper summarizes experiences and results of productively using knowledge discovery and data mining techniques in a large detail bank data. Data mining is the process of extracting patterns from data. We review prior literature on mobile payments, analyze the various factors that impact mobile payment services markets, and suggest directions for future research in this risk management field. Our research work demonstrates the effectiveness and efficiency of data mining in analysis of retailing bank performance. We use classification and regression tree learning algorithm for proposing a customer adoption model of mobile banking according to some personal characteristics of customers.