EFFECTS OF RESIDENTIAL SEGREGATION AND NEIGHBORHOOD OPPORTUNITY STRUCTURE ON THE EMPLOYMENT OF BLACK AND WHITE YOUTH

The object of this article is to consider the impact of local labor market opportunities on the employment of youth, and to evaluate the extent to which residential segregation is detrimental to the employment of young blacks. In the study, labor force statistics for white and black youth are related to job availability estimates derived from Dun and Bradstreet business data for 74 neighborhood communities in the city of Chicago. The findings underscore the unique role of local labor markets, especially for youth enrolled in school. Job availability has a strong impact on the employment ratio of blacks, but affects the employment of white youth only slightly. It appears, however, that when job availability is controlled, blacks benefit somewhat from segregation. The implications for job redistribution and its possible effect on the racial employment gap are discussed.     

POPAN-4: enhancements to a system for the analysis of mark-recapture data from open populations

We describe recent developments in the POPAN system for the analysis of mark-recapture data from Jolly-Seber type experiments. The previous versions (POPAN-3 for SUN/OS workstations and POPAN-PC for IBM-PC running DOS or Windows) included general statistics gathering and testing procedures, a wide range of analysis options for estimating population abundance, survival and birth parameters, and a general simulation capability. POPAN-4 adds a very general procedure for fitting constrained models based on a new unified theory for Jolly-Seber models. Users can impose constraints on capture, survival and birth rates over time and/or across attribute groups (e.g. sex or age groups) and can model these rates using covariate models involving auxiliary variables (e.g. sampling effort).     

Fitting Weibull duration models with random effects

Duration time models often should include correlated failure times, due to clustered data. These random effects hierarchical models sometimes are called frailty models when used for survival analyses. The data analyzed here involve such correlations because patient level outcomes (the times until graft failure following kidney transplantation) are observed, but patients are clustered in different transplant centers. We describe fitting such models by combining two kinds of software, one for parametric survival regression models, and the other for doing Poisson regression in a hierarchical setting. The latter is implemented by using PRIMM (Poisson Regression and Interactive Multilevel Modeling) methods and software (Christiansen & Morris, 1994a). An illustrative example for profiling data is included withk=11 kidney transplant centers andN=412 patients.     

The analysis of multiple ties in longitudinal egocentric network data: A case study on bidirectional relationships between trust and drug use

We extend multi-level models to examine single egocentric network ties to the joint analysis of paired dynamic ties. Two analytic challenges are addressed. First, inference needs to account for multiple layers of nesting: ties are nested within pairs, pairs are nested within time points, and time points are nested within egos. Second, the focus is on the relationship between two dynamic ties; specification of outcome and predictor may be difficult. Instead, we treat both ties as outcomes. Our approach is used to analyze trust and reported drug use between egos and alters over time in a Bayesian framework.     

Service tasks of board of directors: A literature review and research agenda in an era of new governance practices

In their seminal review article on board of directors, Johnson, Daily, and Ellstrand (1996) distinguished between the control, service, and resource dependence tasks of the board and called for a stronger focus on board service tasks. Following this call, service tasks of boards have been subject to increased scholarly attention, with new theoretical perspectives and methods introduced. This paper aims at presenting the current state of research on board service tasks, departing from, and building on, the contribution of Johnson and colleagues. In doing so, we employ an Input-Process-Output-Context framework and craft an agenda for how future research could accommodate new governance practices and progress the field. Our review is relevant and timely as studies on the subject are gaining traction both in corporate governance and general management journals. Furthermore, our review on board service tasks proposes new alternative approaches to studying corporate governance which are especially appropriate in times in which a rethink of corporate governance frameworks and concepts is urgently needed.     

State of public relations education in the United States: 2006 report on a national survey of executives and academics

A survey of 312 public relations executives and educators examined how well practitioners and instructors perceive public relations students to be prepared for the practice, the content and value of public relations curricula and, the future of public relations education in the United States. Results are largely consistent with those from a slightly smaller 1998 survey, suggesting that the views of both groups are consistent over time and providing the first two data points in what it is hoped will develop into a longitudinal line of research addressing public relations education. Judgments regarding the desired characteristics among job applicants and essential curriculum content were extremely similar between the practitioner and educator groups with both wanting more emphasis on research, ethics and strategic planning as the field moves from a low-paid technical emphasis toward a much better paid strategic planning and research emphasis.     

The horizons of technological control: automated surveillance in the New York subway

Surveillance technologies may be capable of monitoring a domain, but they need a sufficiently orderly domain to monitor. This article examines the secretive effort to institute artificial-intelligence-based ‘smart surveillance’ in the New York subway, using object- and pattern-recognition algorithms to identify dangerous activities in video feeds, such as a person abandoning a package. By considering the necessary preconditions for computer vision systems to recognize patterns and objects, I show how smart surveillance was challenged by the lack of visual and social uniformities necessary for smart surveillance systems to make its fine-toothed distinctions. In spite of vast resources and involvement of a major military contractor, the project was eventually deemed a failure. Although problems in computer vision are being incrementally solved, those improvements do not yet add up to a holistic technology capable of parsing the real-world ambiguity of open-ended settings which do not meet the assumptions of the detection algorithms. In the absence of technologies that can handle the actual mess, the world itself must cooperate, but it often does not. The article demonstrates the importance of looking beyond the claims of technical efficacy in the study of security and surveillance to discover how technologies of inspection and control actually work, as a means to cut through the heavy rhetorical packaging in which they are sold to their publics.     

A Novel Approach to Chemical Mixture Risk Assessment—Linking Data from Population‐Based Epidemiology and Experimental Animal Tests

Humans are continuously exposed to chemicals with suspected or proven endocrine disrupting chemicals (EDCs). Risk management of EDCs presents a major unmet challenge because the available data for adverse health effects are generated by examining one compound at a time, whereas real‐life exposures are to mixtures of chemicals. In this work, we integrate epidemiological and experimental evidence toward a whole mixture strategy for risk assessment. To illustrate, we conduct the following four steps in a case study: (1) identification of single EDCs (“bad actors”)—measured in prenatal blood/urine in the SELMA study—that are associated with a shorter anogenital distance (AGD) in baby boys; (2) definition and construction of a “typical” mixture consisting of the “bad actors” identified in Step 1; (3) experimentally testing this mixture in an in vivo animal model to estimate a dose–response relationship and determine a point of departure (i.e., reference dose [RfD]) associated with an adverse health outcome; and (4) use a statistical measure of “sufficient similarity” to compare the experimental RfD (from Step 3) to the exposure measured in the human population and generate a “similar mixture risk indicator” (SMRI). The objective of this exercise is to generate a proof of concept for the systematic integration of epidemiological and experimental evidence with mixture risk assessment strategies. Using a whole mixture approach, we could find a higher rate of pregnant women under risk (13%) when comparing with the data from more traditional models of additivity (3%), or a compound‐by‐compound strategy (1.6%).     

Organizational Reputation and the Securities and Exchange Commission's Failed Regulatory Revolution

When do regulatory innovations fail? I provide a novel organizations‐based answer to this question by developing an institutional‐reputational approach to regulatory politics. Regulators cannot hope to monitor the vast majority of market activities, so they must rely on the regulated to condition their behavior on the regulator's reputation: beliefs and expectations concerning the regulator's goals and capabilities. Regulators thus pursue daily activities while being mindful of how these activities will shape their reputation and thus their ability to achieve future goals. However, even long‐standing reputations are rendered fragile when rival actors use the organization's reputation to cross‐purposes. Thus, while reputation represents a major source of power, reputation also proves fragile when organizations face conflicting reputational demands. The fragility of reputations provides a novel explanation of an understudied phenomenon: failed regulatory revolutions. I develop this theory through the analysis of innovative Securities and Exchange Commission activity in disclosure law following the Watergate investigation.