Virus interruptus: An Arendtian exploration of political world‐building in pandemic times

Building upon a series of blog posts and conversations, two feminist scholars explore how political community, trust, responsibility and solidarity are affected by the COVID‐19 pandemic. We explore the ways in which we can engage in political world‐building during pandemic times through the work of Hannah Arendt. Following Arendt’s notion of the world as the space for human togetherness, we ask: how can we respond to COVID‐19’s interruptions to the familiarity of daily life and our relationship to public space? By extending relational accounts of public health and organizational ethics, we critique a narrow view of solidarity that focuses on individual compliance with public health directives. Instead, we argue that solidarity involves addressing structural inequities, both within public health and our wider community. Finally, we suggest possibilities for political world‐building by considering how new forms of human togetherness might emerge as we forge a collective ‘new normal’.     

Decisions,Science, and Values: Crafting Regulatory Alternatives Analysis

Emerging “prevention‐based” approaches to chemical regulation seek to minimize the use of toxic chemicals by mandating or directly incentivizing the adoption of viable safer alternative chemicals or processes. California and Maine are beginning to implement such programs, requiring manufacturers of consumer products containing certain chemicals of concern to identify and evaluate potential safer alternatives. In the European Union, the REACH program imposes similar obligations on manufacturers of certain substances of very high concern. Effective prevention‐based regulation requires regulatory alternatives analysis (RAA), a methodology for comparing and evaluating the regulated chemical or process and its alternatives across a range of relevant criteria. RAA has both public and private dimensions. To a significant degree, alternatives analysis is an aspect of product design; that is, the process by which private industry designs the goods it sells. Accordingly, an RAA method should reflect the attributes of well‐crafted product design tools used by businesses. But RAA adds health and environmental objectives to the mix of concerns taken into account by the product designer. Moreover, as part of a prevention‐based regulatory regime, it implicates important public values such as legitimacy, equity, public engagement, and accountability. Thus, an RAA should reflect both private standards and public values, and be evaluated against them. This article adopts that perspective, identifying an integrated set of design principles for RAA, and illustrating the application of those principles.     

For an integrative theory of social behaviour: Theorising with and beyond rational choice theory

Most sociologists are not content with merely relating macrosocial phenomena to preceding macrosocial causes in their causal explanations of social phenomena. Instead they are seeking to provide (non‐reductive) microfoundations with which they can corroborate and make understandable the connection between macrosocial phenomena. In order to do so a theory (or theories) of human action is required. One such theory, rational choice theory (RCT), has long been viewed with strong suspicion in sociology. I show such suspicion to be partially justified. RCT cannot be a general theory of social behaviour. Nonetheless, there are important insights in various versions of RCT that should not be discarded. In order to improve upon RCT and move toward a more unified or integrative theory of action social‐psychological research has to be taken note of. I demonstrate how dual‐process theories and the research on heuristics can help sociologists move beyond RCT without contradicting some of its more basic insights.     

Student budgets and widening participation: Comparative experiences of finance in low and higher income undergraduates at a northern red brick university

Drawing on a thematic analysis of longitudinal qualitative data (n_total = 118), this article takes a “whole student lifecycle” approach to examine how lower and higher income students at an English northern red brick university variously attempted to manage their individual budgets. It explores how students reconcile their income—in the form of loans, grants, and bursaries—with the cost of living. Four arenas of interest are described: planning, budgeting, and managing “the student loan”; disruptions to financial planning; the role of familial support; and strategies of augmenting the budget. In detailing the micro‐level constraints on the individual budgets of lower and higher income undergraduates, the article highlights the importance of non‐repayable grants and bursaries in helping to sustain meaningful participation in higher tariff, more selective, higher education institutions. It also supports an emerging body of literature that suggests that the continuing amendments to the system of funding higher education in England are unlikely to address inequality of access, participation, and outcome.     

Modeling Finite‐Time Failure Probabilities in Risk Analysis Applications

In this article, we introduce a framework for analyzing the risk of systems failure based on estimating the failure probability. The latter is defined as the probability that a certain risk process, characterizing the operations of a system, reaches a possibly time‐dependent critical risk level within a finite‐time interval. Under general assumptions, we define two dually connected models for the risk process and derive explicit expressions for the failure probability and also the joint probability of the time of the occurrence of failure and the excess of the risk process over the risk level. We illustrate how these probabilistic models and results can be successfully applied in several important areas of risk analysis, among which are systems reliability, inventory management, flood control via dam management, infectious disease spread, and financial insolvency. Numerical illustrations are also presented.     

Reducing the Risk of Injury from Table Saw Use: The Potential Benefits and Costs of Automatic Protection

The use of table saws in the United States is associated with approximately 28,000 emergency department (ED) visits and 2,000 cases of finger amputation per year. This article provides a quantitative estimate of the economic benefits of automatic protection systems that could be designed into new table saw products. Benefits are defined as reduced health‐care costs, enhanced production at work, and diminished pain and suffering. The present value of the benefits of automatic protection over the life of the table saw are interpreted as the switch‐point cost value, the maximum investment in automatic protection that can be justified by benefit‐cost comparison. Using two alternative methods for monetizing pain and suffering, the study finds switch‐point cost values of $753 and $561 per saw. These point estimates are sensitive to the values of inputs, especially the average cost of injury. The various switch‐point cost values are substantially higher than rough estimates of the incremental cost of automatic protection systems. Uncertainties and future research needs are discussed.     

A Decision Framework for Managing Risk to Airports from Terrorist Attack

This article presents an asset‐level security risk management framework to assist stakeholders of critical assets with allocating limited budgets for enhancing their safety and security against terrorist attack. The proposed framework models the security system of an asset, considers various threat scenarios, and models the sequential decision framework of attackers during the attack. Its novel contributions are the introduction of the notion of partial neutralization of attackers by defenders, estimation of total loss from successful, partially successful, and unsuccessful actions of attackers at various stages of an attack, and inclusion of the effects of these losses on the choices made by terrorists at various stages of the attack. The application of the proposed method is demonstrated in an example dealing with security risk management of a U.S. commercial airport, in which a set of plausible threat scenarios and risk mitigation options are considered. It is found that a combination of providing blast‐resistant cargo containers and a video surveillance system on the airport perimeter fence is the best option based on minimum expected life‐cycle cost considering a 10‐year service period.     

Risk‐Cost‐Benefit Analysis for Transportation Corridors with Interval Uncertainties of Heterogeneous Data

Access management, which systematically limits opportunities for egress and ingress of vehicles to highway lanes, is critical to protect trillions of dollars of current investment in transportation. This article addresses allocating resources for access management with incomplete and partially relevant data on crash rates, travel speeds, and other factors. While access management can be effective to avoid crashes, reduce travel times, and increase route capacities, the literature suggests a need for performance metrics to guide investments in resource allocation across large corridor networks and several time horizons. In this article, we describe a quantitative decision model to support an access management program via risk‐cost‐benefit analysis under data uncertainties from diverse sources of data and expertise. The approach quantifies potential benefits, including safety improvement and travel time savings, and costs of access management through functional relationships of input parameters including crash rates, corridor access point densities, and traffic volumes. Parameter uncertainties, which vary across locales and experts, are addressed via numerical interval analyses. This approach is demonstrated at several geographic scales across 7,000 kilometers of highways in a geographic region and several subregions. The demonstration prioritizes route segments that would benefit from risk management, including (i) additional data or elicitation, (ii) right‐of‐way purchases, (iii) restriction or closing of access points, (iv) new alignments, (v) developer proffers, and (vi) etc. The approach ought to be of wide interest to analysts, planners, policymakers, and stakeholders who rely on heterogeneous data and expertise for risk management.     

Application of the Hyper‐Poisson Generalized Linear Model for Analyzing Motor Vehicle Crashes

The hyper‐Poisson distribution can handle both over‐ and underdispersion, and its generalized linear model formulation allows the dispersion of the distribution to be observation‐specific and dependent on model covariates. This study's objective is to examine the potential applicability of a newly proposed generalized linear model framework for the hyper‐Poisson distribution in analyzing motor vehicle crash count data. The hyper‐Poisson generalized linear model was first fitted to intersection crash data from Toronto, characterized by overdispersion, and then to crash data from railway‐highway crossings in Korea, characterized by underdispersion. The results of this study are promising. When fitted to the Toronto data set, the goodness‐of‐fit measures indicated that the hyper‐Poisson model with a variable dispersion parameter provided a statistical fit as good as the traditional negative binomial model. The hyper‐Poisson model was also successful in handling the underdispersed data from Korea; the model performed as well as the gamma probability model and the Conway‐Maxwell‐Poisson model previously developed for the same data set. The advantages of the hyper‐Poisson model studied in this article are noteworthy. Unlike the negative binomial model, which has difficulties in handling underdispersed data, the hyper‐Poisson model can handle both over‐ and underdispersed crash data. Although not a major issue for the Conway‐Maxwell‐Poisson model, the effect of each variable on the expected mean of crashes is easily interpretable in the case of this new model.