A sociology of hackers

Illicit computer intruders, or hackers, are often thought of as pathological individuals rather than as members of a community. However, hackers exist within social groups that provide expertise, support, training, journals and conferences. This article outlines this community to establish the nature of hacking within ‘information societies’. To delineate a ‘sociology of hackers’, an introduction is provided to the nature of computer–mediated communication and the act of computer intrusion, the hack. Following this the hacking community is explored in three sections. First, a profile of the number of hackers and hacks is provided by exploring available demographics. Second, an outline of its culture is provided through a discussion of six different aspects of the hacking community. The six aspects are technology, secrecy, anonymity, membership fluidity, male dominance and motivations. Third, an exploration of the community's construction of a boundary, albeit fluid, between itself and its other, the computer security industry, is provided. This boundary is constructed through metaphors whose central role is to establish the ethical nature of hacking. Finally, a conclusion that rejects any pathologisation of hackers is offered.     

Interest Organizations,Information, and Policy Innovation in the U.S. Congress1 2

Interest organizations are hypothesized to strongly affect public policy, but the evidence that they do so is mixed. This article argues that one reason for the disparity is a gap between theory and research: theory suggests that information provided by interest organizations should strongly influence elected officials, but there is no systematic research on its impact. We examine a potentially important source of information for members of the U.S. Congress—testimony at committee hearings—to ascertain if it affects the enactment of policy proposals. The data, based on content analysis of almost 1,000 testimonies on a stratified random sample of policy proposals, describe who testifies, their arguments, and the evidence they provide. Supporters of a proposal emphasize the importance of the problem being addressed, while opponents claim the proposed policy will be ineffective and try to reframe the debate. Information—particularly information regarding policy effectiveness—does affect the likelihood that a policy proposal will be enacted.     

Describing the Dynamics of Attention to TV Commercials: A Hierarchical Bayes Analysis of the Time to Zap an Ad

This paper provides insights into the dynamics of attention to TV commercials via an analysis of the length of time that commercials are viewed before being 'zapped'. The model, which incorporates a flexible baseline hazard rate and captures unobserved heterogeneity across both consumers and commercials using a hierarchical Bayes approach, is estimated on two datasets in which commercial viewing is captured by a passive online device that continually monitors a household's TV viewing. Consistent with previous findings in psychology about the nature of attentional engagement in TV viewing, baseline hazard rates are found to be non-monotonic. In addition, the data show considerable ad-to-ad and household-to-household heterogeneity in zapping behavior. While one of the datasets contains some information on characteristics of the ads, these data do not reveal any firm links between the ad heterogeneity and the ad characteristics. A number of methodological and computational issues arise in the hierarchical Bayes analysis.     

Risk,Media, and Stigma at Rocky Flats

Public responses to nuclear technologies are often strongly negative. Events, such as accidents or evidence of unsafe conditions at nuclear facilities, receive extensive and dramatic coverage by the news media. These news stories affect public perceptions of nuclear risks and the geographic areas near nuclear facilities. One result of these perceptions, avoidance behavior, is a form of "technological stigma" that leads to losses in property values near nuclear facilities. The social amplification of risk is a conceptual framework that attempts to explain how stigma is created through media transmission of information about hazardous places and public perceptions and decisions. This paper examines stigma associated with the U.S. Department of Energy's Rocky Flats facility, a major production plant in the nation's nuclear weapons complex, located near Denver, Colorado. This study, based upon newspaper analyses and a survey of Denver area residents, finds that the social amplification theory provides a reasonable framework for understanding the events and public responses that took place in regard to Rocky Flats during a 6-year period, beginning with an FBI raid of the facility in 1989.     

A Full Bayesian Non-parametric Analysis Involving a Neutral to the Right Process

Implementation of a full Bayesian non-parametric analysis involving neutral to the right processes (apart from the special case of the Dirichlet process) has been difficult for two reasons: first, the posterior distributions are complex and therefore only Bayes estimates (posterior expectations) have previously been presented; secondly, it is difficult to obtain an interpretation for the parameters of a neutral to the right process. In this paper we extend Ferguson & Phadia (1979) by presenting a general method for specifying the prior mean and variance of a neutral to the right process, providing the interpretation of the parameters. Additionally, we provide the basis for a full Bayesian analysis, via simulation, from the posterior process using a hybrid of new algorithms that is applicable to a large class of neutral to the right processes (Ferguson & Phadia only provide posterior means). The ideas are exemplified through illustrative analyses.     

Are We Playing the Same Game?: Publishing Task Environments and Research Productivity Among Management Specialists

Archival data on over 15,000 contributors to 33management journals are used to examine productivitydifferences among scholars in different areas ofmanagement. The results suggest that a fragmentedpublication network offers specialists from different areasdissimilar publication opportunities and experiences,and may contribute to varying levels of publicationproductivity among authors. The implications of our results for future research and facultyevaluation processes are explored.     

Trust in surveys and games – A methodological contribution on the influence of money and location

This paper explores methods to study trust. In a variety of settings, answers to survey questions and choices in a trust game are obtained from student sample pools. Some subjects are approached by mail and execute their task at home whereas others participate in classroom experiments. No differences between the results obtained by these methods are observed. Furthermore, one additional group plays the trust game with purely hypothetical payments, and another receives random lottery payments. This changes trust behavior dramatically, whereas trustworthiness is unaffected. Subjects without any financial incentives exhibit less trust and their trust choices are significantly correlated with survey trust answers. There is no such correlation for the corresponding choices with real payments.     

Regression Modelling of Disease Risk in Relation to Point Sources

We describe a class of models for the investigation of possible raised risk of disease around putative sources of environmental pollution. An adaptation of the point process method suggested by Diggle and Rowlingson is presented, allowing the use of routinely available aggregated data and incorporating the more general distance–risk model suggested by Elliott and co-workers. An application to data on cancers of the stomach around municipal solid waste incinerators is presented.     

Forecasting mortality rates via density ratio modeling

The authors propose a semiparametric approach to modeling and forecasting age‐specific mortality in the United States. Their method is based on an extension of a class of semiparametric models to time series. It combines information from several time series and estimates the predictive distribution conditional on past data. The conditional expectation, which is the most commonly used predictor in practice, is the first moment of this distribution. The authors compare their method to that of Lee and Carter.