Did the escalation of the financial crisis of 2008 affect the perception of immigration-related threats? A natural experiment

In this paper, we apply a natural experiment approach, comparing specific data from the European Values Study prior to and after the escalation of the financial crisis in 2008. The aim is to disentangle the short-term effect of the crisis on the relationship between social vulnerability and immigrant-related threat perceptions for the residents of Luxembourg (natives and foreign nationals). Propensity score matching is used to ensure the balanced composition of the control group and treated group with regard to the observed covariates. The results reveal that vulnerable foreign nationals demonstrated lower perceptions of immigration-related threats after the escalation of the crisis than their pre-crisis counterparts. No significant effect of the escalation of the crisis was found among Luxembourg nationals.     

A Discussion of Findings and Their Possible Implications from a Workshop on Bioterrorism Threat Assessment and Risk Management

In November 2001, the Monterey Institute of International Studies convened a workshop on bioterrorism threat assessment and risk management. Risk assessment practitioners from various disciplines, but without specialized knowledge of terrorism, were brought together with security and intelligence threat analysts to stimulate an exchange that could be useful to both communities. This article, prepared by a subset of the participants, comments on the workshop's findings and their implications and makes three recommendations, two short term (use of threat assessment methodologies and vulnerability analysis) and one long term (application of quantitative risk assessment and modeling), regarding the practical application of risk assessment methods to bioterrorism issues.     

农村家庭“因教致贫”现象解读与政策建议——基于脆弱性理论视角

教育具有促进政治进步、经济发展、文化传承的正向功能。然而,"知识改变命运"作为一个真理性的命题,在我国广大农村地区似乎成为了一个悖论,出现了较大面积的"因教致贫"反常现象。农村"因教致贫"问题具有多维度性和多层面性,是一个复杂的系统性问题。一般来说,此问题涉及到农村的经济基础、自然环境、政策环境以及社会环境等各个层面,农村家庭的抗风险能力差决定了农民家庭脆弱性程度较高,较高的脆弱性是导致"因教致贫"的真正原因。因此,从就学就业先后顺序出发,引入脆弱性理论,分析"因教致贫"动态形成过程中的脆弱性因子,对农村地区"因教致贫"现象进行深入探讨和研究,并提出相应的政策建议。     

What if gender became an essential,standard element of Vulnerability Assessments?

Vulnerability Assessments (VAs) can be useful tools for providing key insights for non-government organisations and other development actors, including governments. Not only can they provide an extensive, ‘landscape-wide’ understanding of vulnerability and its underlying causes in a specific context, but this understanding can be jointly owned by all participants. They can thus be used for designing risk reduction and resilience-building measures, programmes, or projects that affect specific groups within a community or the landscape. Beyond that, VAs can provide a platform that promotes interaction among otherwise disconnected stakeholders, as well as the evidence and argumentation for community groups to engage in advocacy with local and municipal/district authorities. This article draws on our combined experience as development practitioners, and considers what we have learnt about the importance of integrating gender issues into VAs.     

基于stackelberg博弈的供应链企业间信息安全决策分析

针对网络系统不同的脆弱性,通过建模分析了网络暴露程度、黑客攻击概率、黑客入侵概率、安全投资效率等因素对企业的网络安全投资策略的影响,研究了一定预算约束下的企业网络安全投资策略。研究表明：在企业网络系统防御随机攻击能力较强,防御定向攻击能力较弱的情况下,当安全投资总额非常大的时候,对随机攻击类型的投资分配应随着安全投资总额的增大而增大,对定向攻击类型的投资分配应随着安全投资总额的增大而减小;当安全投资总额非常小时,投资分配情况视网络暴露程度的大小而定。     

协同治理对城市矿产开发不良绩效的解决机制——基于产业链脆弱性的视角

城市矿产开发是推进生态文明建设和打造“无废城市”的重要抓手。从产业链脆弱性视角构建协同治理影响城市矿产开发不良绩效的理论模型,并借助国家城市矿产示范基地的312份样本数据,运用结构方程模型和调节回归分析开展实证研究。研究表明：协同治理的协同主体素质、协同结构质量和协同机制效力三个维度对城市矿产开发不良绩效具有显著负向影响效应;动态协同能力在两者关系中发挥完全中介作用,协同感知力、协同适应力和协同恢复力三个构成维度在两者关系中产生显著但程度有别的部分中介效应;协同氛围在协同主体素质与动态协同能力间产生负向调节效应,在协同机制效力与动态协同能力间产生正向调节效应,而环境不确定性在动态协同能力与城市矿产开发不良绩效间发挥正向调节作用。这些结论揭示出协同治理解决城市矿产开发不良绩效问题的内在机制,为提升城市矿产开发绩效提供决策参考。     

GIS‐Based Integration of Social Vulnerability and Level 3 Probabilistic Risk Assessment to Advance Emergency Preparedness,Planning, and Response for Severe Nuclear Power Plant Accidents

In the nuclear power industry, Level 3 probabilistic risk assessment (PRA) is used to estimate damage to public health and the environment if a severe accident leads to large radiological release. Current Level 3 PRA does not have an explicit inclusion of social factors and, therefore, it is not possible to perform importance ranking of social factors for risk‐informing emergency preparedness, planning, and response (EPPR). This article offers a methodology for adapting the concept of social vulnerability, commonly used in natural hazard research, in the context of a severe nuclear power plant accident. The methodology has four steps: (1) calculating a hazard‐independent social vulnerability index for the local population; (2) developing a location‐specific representation of the maximum radiological hazard estimated from current Level 3 PRA, in a geographic information system (GIS) environment; (3) developing a GIS‐based socio‐technical risk map by combining the social vulnerability index and the location‐specific radiological hazard; and (4) conducting a risk importance measure analysis to rank the criticality of social factors based on their contribution to the socio‐technical risk. The methodology is applied using results from the 2012 Surry Power Station state‐of‐the‐art reactor consequence analysis. A radiological hazard model is generated from MELCOR accident consequence code system, translated into a GIS environment, and combined with the Center for Disease Control social vulnerability index (SVI). This research creates an opportunity to explicitly consider and rank the criticality of location‐specific SVI themes based on their influence on risk, providing input for EPPR.     

An Optimization‐Based Framework for the Identification of Vulnerabilities in Electric Power Grids Exposed to Natural Hazards

This article proposes a novel mathematical optimization framework for the identification of the vulnerabilities of electric power infrastructure systems (which is a paramount example of critical infrastructure) due to natural hazards. In this framework, the potential impacts of a specific natural hazard on an infrastructure are first evaluated in terms of failure and recovery probabilities of system components. Then, these are fed into a bi‐level attacker–defender interdiction model to determine the critical components whose failures lead to the largest system functionality loss. The proposed framework bridges the gap between the difficulties of accurately predicting the hazard information in classical probability‐based analyses and the over conservatism of the pure attacker–defender interdiction models. Mathematically, the proposed model configures a bi‐level max‐min mixed integer linear programming (MILP) that is challenging to solve. For its solution, the problem is casted into an equivalent one‐level MILP that can be solved by efficient global solvers. The approach is applied to a case study concerning the vulnerability identification of the georeferenced RTS24 test system under simulated wind storms. The numerical results demonstrate the effectiveness of the proposed framework for identifying critical locations under multiple hazard events and, thus, for providing a useful tool to help decisionmakers in making more‐informed prehazard preparation decisions.     

Perception of Climate Risk among Rural Farmers in Vietnam: Consistency within Households and with the Empirical Record

Rural farmers in Vietnamese communes perceive climate risk and potential impacts on livelihood within a complex context that may influence individual and household decisions. In a primary survey of 1,145 residents of the Thach Ha district of Ha Tinh province, we gathered data regarding perception about stability in climate, potential risks to livelihood, demographic characteristics, orientation toward risk, and interest in expanding economic activity. Temporal analysis of meteorological and economic indicator data forms an empirical basis for comparison with human perception. We ask the basic question: Are rural farmers’ perceptions of climate consistent with the historical record and reproducible within households? We find that respondents do perceive climate anomalies, with some anchoring on recent extreme events as revealed by climate observational data, and further that spouses disproportionately share perceptions relative to randomly simulated pairings. To put climate‐related risk perception in a larger context, we examine patterns across a range of risks to livelihood faced by farmers (livestock disease, pests, markets, health), using dimension reduction techniques. We find that our respondents distinguish among potential causes of low economic productivity, with substantial emphasis on climate‐related impacts. They do not express uniform concern across risks, but rather average patterns reveal common modes and distinguish climate concern. Still, among those expressing concern about climate‐related risks to livelihood we do not find an association with expressed intention to pursue changes in economic activity as a risk management response.     

Resource Distribution in Multiple Attacks with Imperfect Detection of the Attack Outcome

This article extends the previous research of consecutive attacks strategy by assuming that an attacker observes the outcome of each attack imperfectly. With given probabilities it may wrongly identify a destroyed target as undestroyed, and wrongly identify an undestroyed target as destroyed. The outcome of each attack is determined by a contest success function that depends on the amount of resources allocated by the defender and the attacker to each attack. The article suggests a probabilistic model of the multiple attacks and analyzes how the target destruction probability and the attacker's relative resource expenditure are impacted by the two probabilities of incorrect observation, the attacker's and defender's resource ratio, the contest intensity, the number of attacks, and the resource distribution across attacks. We analyze how the attacker chooses the number of attacks, the attack stopping rule, and the optimal resource distribution across attacks to maximize its utility.