胡塞尔生活世界的两种含义——兼谈欧洲科学与人的危机及其克服

胡塞尔所说的“生活世界”有两种含义:一是作为经验实在的客观生活世界,一是作为纯粹先验现象的主观生活世界,二者之间隔着一道先验还原的界限。不同意义上的“生活世界”与科学及人的生存的关系也不同:在胡塞尔看来,前者是近代科学产生的基础,也是造成科学“危机”与人的“危机”的根源;后者则有可能为我们提供一条克服这种危机的途径。     

基于Bayes推理的灾害演化GERT网络模型研究

灾害、衍生和次生灾害及其相互耦合使得灾情恶化,作为灾害对抗力量的抢险、避险、控制的救险等措施使得灾害向灾情减轻的方向转化,本文对灾害的这一动态演化过程进行描述,建立一种综合考虑灾害的自然演化与抢险救灾行动的基于Bayes推理的灾害演化GERT(Graph Evaluation and Review Technique)网络模型;把GERT网络方法和贝叶斯推理工具相结合,根据获得的新信息,对GERT网络中活动参数进行动态修正,对灾害的演化路径,各种主要状态的演化概率和时间进行动态预测、预警与评价;对衍生与次生灾害、抢险救灾行动等外界行为对系统演化的影响进行定性与定量分析,并给出定量评价结论。本文提供了灾害演化定性与定量结合的分析框架与工具,揭示灾害演化机理,为灾害发展态势的预测、预警与评价提供了一种新的研究方法和研究思路。     

管理科学与工程学科基金项目资助和SCI论文发表情况分析

系统地统计了2003～2008年国家自然科学基金委员会管理科学部管理科学与工程学科面上项目和青年项目受资助的总体情况,分析了各个子学科类别的资助状况和发表SCI论文情况,同时分析比较了国家"十一五"与"十五"期间的资助项目情况和发表SCI论文数量情况,找出其中存在的问题并对其原因进行了分析.最后,依据国家自然科学基金"十一五"发展战略,提出今后国家自然科学基金资助策略和建议.     

中国自然利率的测算——基于SVAR方法

本文首先利用SVAR模型估计我国的自然利率水平,并在此基础上计算实际利率缺口,然后对实际利率缺口与通货膨胀率的关系进行研究。研究发现:我国实际利率长期低于自然利率;实际利率缺口与通货膨胀率负相关,实际利率缺口变大,通货膨胀率变小,反之则相反。分析表明,实际利率缺口作为宏观经济的重要指标能够反映通货膨胀的变化,利率政策制定部门应把实际利率缺口纳入到政策工具中。     

How Plant Managers' Experiences and Attitudes Toward Sustainability Relate to Operational Performance

Managers are increasingly faced with pressure to think not just about profits, but also about their organization's environmental and social performance. This research provides a first examination of operational managers' experiences with and attitudes about employee well‐being and environmental issues, how these factors impact employee well‐being and environmental performance, and how the three performance measures interrelate. We use violations of Occupational Safety and Health Administration regulations and Toxic Release Inventory reports of emissions as proxies for employee well‐being and environmental performance. Our findings suggest that operational managers do not (yet) think in sustainability terms. However, employee well‐being and environmental performance do interact in a significant way with operational performance. Hence, operational managers would benefit from a more complete understanding of the relationships among the elements of the triple bottom line.     

Perceptions of Risk and Vulnerability Following Exposure to a Major Natural Disaster: The Calgary Flood of 2013

Many studies have examined the general public's flood risk perceptions in the aftermath of local and regional flooding. However, relatively few studies have focused on large‐scale events that affect tens of thousands of people within an urban center. Similarly, in spite of previous research on flood risks, unresolved questions persist regarding the variables that might influence perceptions of risk and vulnerability, along with management preferences. In light of the opportunities presented by these knowledge gaps, the research reported here examined public perceptions of flood risk and vulnerability, and management preferences, within the city of Calgary in the aftermath of extensive flooding in 2013. Our findings, which come from an online survey of residents, reveal that direct experience with flooding is not a differentiating factor for risk perceptions when comparing evacuees with nonevacuees who might all experience future risks. However, we do find that judgments about vulnerability—as a function of how people perceive physical distance—do differ according to one's evacuation experience. Our results also indicate that concern about climate change is an important predictor of flood risk perceptions, as is trust in government risk managers. In terms of mitigation preferences, our results reveal differences in support for large infrastructure projects based on whether respondents feel they might actually benefit from them.     

Online patient feedback as a safety valve: An automated language analysis of unnoticed and unresolved safety incidents

Safety reporting systems are widely used in healthcare to identify risks to patient safety. But, their effectiveness is undermined if staff do not notice or report incidents. Patients, however, might observe and report these overlooked incidents because they experience the consequences, are highly motivated, and independent of the organization. Online patient feedback may be especially valuable because it is a channel of reporting that allows patients to report without fear of consequence (e.g., anonymously). Harnessing this potential is challenging because online feedback is unstructured and lacks demonstrable validity and added value. Accordingly, we developed an automated language analysis method for measuring the likelihood of patient-reported safety incidents in online patient feedback. Feedback from patients and families (n = 146,685, words = 22,191,427, years = 2013–2019) about acute NHS trusts (hospital conglomerates; n = 134) in England were analyzed. The automated measure had good precision (0.69) and excellent recall (0.98) in identifying incidents; was independent of staff-reported incidents (r = −0.04 to 0.19); and was associated with hospital-level mortality rates (z = 3.87; p < 0.001). The identified safety incidents were often reported as unnoticed (89%) or unresolved (21%), suggesting that patients use online platforms to give visibility to safety concerns they believe have been missed or ignored. Online stakeholder feedback is akin to a safety valve; being independent and unconstrained it provides an outlet for reporting safety issues that may have been unnoticed or unresolved within formal channels.     

Media Disaster Reporting Effects on Public Risk Perception and Response to Escalating Tornado Warnings: A Natural Experiment

Previous research has evaluated public risk perception and response to a natural hazards in various settings; however, most of these studies were conducted either with a single scenario or after a natural disaster struck. To better understand the dynamic relationships among affect, risk perception, and behavioral intentions related to natural disasters, the current study implements a simulation scenario with escalating weather intensity, and includes a natural experiment allowing comparison of public response before and after a severe tornado event with extensive coverage by the national media. The current study also manipulated the display of warning information, and investigated whether the warning system display format influences public response. Results indicate that (1) affect, risk perception, and behavioral intention escalated as weather conditions deteriorated, (2) responses at previous stages predicted responses at subsequent stages of storm progression, and (3) negative affect predicted risk perception. Moreover, risk perception and behavioral intention were heightened after exposure to the media coverage of an actual tornado disaster. However, the display format manipulation did not influence behavioral responses. The current study provides insight regarding public perception of predisaster warnings and the influence of exposure to media coverage of an actual disaster event.     

Quantal Risk Assessment Database: A Database for Exploring Patterns in Quantal Dose‐Response Data in Risk Assessment and its Application to Develop Priors for Bayesian Dose‐Response Analysis

Quantitative risk assessments for physical, chemical, biological, occupational, or environmental agents rely on scientific studies to support their conclusions. These studies often include relatively few observations, and, as a result, models used to characterize the risk may include large amounts of uncertainty. The motivation, development, and assessment of new methods for risk assessment is facilitated by the availability of a set of experimental studies that span a range of dose‐response patterns that are observed in practice. We describe construction of such a historical database focusing on quantal data in chemical risk assessment, and we employ this database to develop priors in Bayesian analyses. The database is assembled from a variety of existing toxicological data sources and contains 733 separate quantal dose‐response data sets. As an illustration of the database's use, prior distributions for individual model parameters in Bayesian dose‐response analysis are constructed. Results indicate that including prior information based on curated historical data in quantitative risk assessments may help stabilize eventual point estimates, producing dose‐response functions that are more stable and precisely estimated. These in turn produce potency estimates that share the same benefit. We are confident that quantitative risk analysts will find many other applications and issues to explore using this database.     

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.