Risk Perception in an Interest Group Context: An Examination of the TMI Restart Issue1

Human response to environmental hazards and risks has been the subject of considerable research by social scientists. Work has traditionally focused on either individual response to the risks of an ongoing or future threat (hazards research), or group and organizational response to a specific disaster event (disaster research). As part of a larger investigation of the restart of the Unit 1 reactor at Three Mile Island (TMI), we examined the response of interest groups active in the restart issue to the continued threat of TMI and to future risks due to restart. After reviewing the restart issue in general, the paper examines the local dimensions of the restart issue from interest group perspectives. A method for defining appropriate issues at the community level is reviewed. We then discuss differences in the perceived local impacts of alternative decisions, and systems of beliefs associated with differing perceptions. Finally, we discuss the implications of interest group versus individual perceptions of local issues for decision making about TMI, in particular, and about technological hazards management, in general. Associated implications for determining socially acceptable risk levels are identified. Our research led us to three major conclusions: (1) in contrast to other types of hazards, interest groups are a critical unit of analysis for understanding how beliefs and behaviors form in response to the presence of technological hazards; (2) the divergence of positions between groups, even though they may have shared the same physical experience, is understandable if not always predictable, (3) the resolution of policy debates where risks are a major focus of the arguments should recognize the legitimacy of these divergent positions by allowing participation of the various interest groups in the decision process. Such participation helps ensure that the decision strategy is responsive to local concerns, thereby increasing the likelihood of acceptance of the ultimate decision and thus producing a publicly acceptable level of risk.     

Characterization of Historical Methane Occurrence Frequencies from U.S. Underground Natural Gas Storage Facilities with Implications for Risk Management,Operations, and Regulatory Policy

Defining a baseline for the frequency of occurrences at underground natural gas storage facilities is critical to maintaining safe operation and to the development of appropriate risk management plans and regulatory approaches. Currently used frequency-estimation methods are reviewed and broadened in this article to include critical factors of cause, severity, and uncertainty that contribute to risk. A Bayesian probabilistic analysis characterizes the aleatoric historical occurrence frequencies given imperfect sampling. Frequencies for the three main storage facility types in the United States (depleted oil-and-gas field storage, aquifer storage, solution-mined salt cavern storage) are generally on the order of 3 to 9 × 10^–2 occurrences, of all causes (surface, well integrity, subsurface integrity) and severities (nuisance, serious, catastrophic), per facility-year. Loss of well integrity is associated with many, but not all, occurrences either within the subsurface or from there up to the surface. The probability of one serious or catastrophic leakage occurrence to the ground surface within the next 10 years, assuming constant number of facilities, is approximately 0.1–0.3% for any facility type. Storage operators and industry regulators can use occurrence frequencies, their associated probabilities and uncertainties, and forecasts of severity magnitudes to better prioritize resources, establish a baseline against which progress toward achieving a reduction target could be measured, and develop more effective mitigation/monitoring/reduction programs in a risk management plan.     

The effects of defamilization and familization measures on the accumulation of retirement income for women in the UK

This article is concerned with the link between the effects of pro-market pension reforms on women and familization/defamilization measures. It aims to contribute to the study of this link in three ways. Firstly, it identifies defamilization/familization measures that have the potential to reduce negative effects of pro-market pension measures on women. Secondly, based on the examples from the United Kingdom, it shows that the government’s willingness to provide sufficient defamilization/familization measures to assist women to deal with the negative effects of the pro-market pension measures should not be taken for granted. Thirdly, it suggests ways for tackling this problem.     

Processes of Religious and Spiritual Influence in Adolescence: Introduction to a Special Section

This paper serves as the lead article introducing the special section of the Journal of Research on Adolescence focused on processes of religious and spiritual influence during adolescence. The purpose of the special section is to review prior theory and research on the processes by which religiosity and spirituality might influence youth outcomes, present original cutting‐edge theory and research on processes of religious and spiritual influence, and point to the most fruitful directions and methodological approaches for future work in the area. The special section is guided by eight research questions which push researchers to go beyond mere bivariate associations between religion/spirituality and youth outcomes to unpacking the processes of influence at work.     

Exploring variation in active network size: Constraints and ego characteristics

Studies of active personal networks have primarily focused on providing reliable estimates of the size of the network. In this study, we examine how compositional properties of the network and ego characteristics are related to variation in network size. There was a negative relationship between mean emotional closeness and network size, for both related and unrelated networks. Further, there was a distinct upper bound on total network size. These results suggest that there are constraints both on the absolute number of individuals that ego can maintain in the network, and also on the emotional intensity of the relationships that ego can maintain with those individuals.     

‘There Isn't Supposed To Be a Speaker Against!’ Investigating Tensions of ‘Safe Space’ and Intra‐Group Diversity for Trade Union Lesbian and Gay Organization

Trade union engagement with the continuing inequalities facing minority groups has been one of the guiding principles of attempts to re‐energize the labour movement in recent years. This article focuses on attempts by six British trade unions to create and maintain separate organizational ‘spaces’ for their lesbian and gay members. Through consideration of group representation within a union framework, the strategy of separate organizing and the complications of representing a diverse membership, this article considers issues of intra‐group diversity and ‘safe space’ for this particular group of members. It concludes that the recognition and actualization of the internally diverse lesbian and gay constituency will be important in the long term for trade unions seeking to renew their pool of potential activists.     

An online classification EM algorithm based on the mixture model

Mixture model-based clustering is widely used in many applications. In certain real-time applications the rapid increase of data size with time makes classical clustering algorithms too slow. An online clustering algorithm based on mixture models is presented in the context of a real-time flaw-diagnosis application for pressurized containers which uses data from acoustic emission signals. The proposed algorithm is a stochastic gradient algorithm derived from the classification version of the EM algorithm (CEM). It provides a model-based generalization of the well-known online k-means algorithm, able to handle non-spherical clusters. Using synthetic and real data sets, the proposed algorithm is compared with the batch CEM algorithm and the online EM algorithm. The three approaches generate comparable solutions in terms of the resulting partition when clusters are relatively well separated, but online algorithms become faster as the size of the available observations increases.