Predicting the Risk of Biological Invasions Using Environmental Similarity and Transport Network Connectedness

Understanding the risk of biological invasions associated with particular transport pathways and source regions is critical for implementing effective biosecurity management. This may require both a model for physical connectedness between regions, and a measure of environmental similarity, so as to quantify the potential for a species to be transported from a given region and to survive at a destination region. We present an analysis of integrated biosecurity risk into Australia, based on flights and shipping data from each global geopolitical region, and an adaptation of the “range bagging” method to determine environmental matching between regions. Here, we describe global patterns of environmental matching and highlight those regions with many physical connections. We classify patterns of global invasion risk (high to low) into Australian states and territories. We validate our analysis by comparison with global presence data for 844 phytophagous insect pest species, and produce a list of high‐risk species not previously known to be present in Australia. We determined that, of the insect pest species used for validation, the species most likely to be present in Australia were those also present in geopolitical regions with high transport connectivity to Australia, and those regions that were geographically close, and had similar environments.     

A Risk-Based Method for Modeling Traffic Fatalities

We describe a risk-based analytical framework for estimating traffic fatalities that combines the probability of a crash and the probability of fatality in the event of a crash. As an illustrative application, we use the methodology to explore the role of vehicle mix and vehicle prevalence on long-run fatality trends for a range of transportation growth scenarios that may be relevant to developing societies. We assume crash rates between different road users are proportional to their roadway use and estimate case fatality ratios (CFRs) for the different vehicle-vehicle and vehicle-pedestrian combinations. We find that in the absence of road safety interventions, the historical trend of initially rising and then falling fatalities observed in industrialized nations occurred only if motorization was through car ownership. In all other cases studied (scenarios dominated by scooter use, bus use, and mixed use), traffic fatalities rose monotonically. Fatalities per vehicle had a falling trend similar to that observed in historical data from industrialized nations. Regional adaptations of the model validated with local data can be used to evaluate the impacts of transportation planning and safety interventions, such as helmets, seat belts, and enforcement of traffic laws, on traffic fatalities.     

A Bayesian method for classification and discrimination

We discuss Bayesian analyses of traditional normal-mixture models for classification and discrimination. The development involves application of an iterative resampling approach to Monte Carlo inference, commonly called Gibbs sampling, and demonstrates routine application. We stress the benefits of exact analyses over traditional classification and discrimination techniques, including the ease with which such analyses may be performed in a quite general setting, with possibly several normal-mixture components having different covariance matrices, the computation of exact posterior classification probabilities for observed data and for future cases to be classified, and posterior distributions for these probabilities that allow for assessment of second-level uncertainties in classification.     

The organizational shaping of collective identity: The case of lesbian and gay film festivals in New York

Using information gathered during fieldwork on New York lesbian and gay film festival organizations, this paper argues that scholarship on identity has not paid sufficient attention to the organizational mediation of collective identity. The shape of collective identity—how internal instabilities and diversities are accommodated, in this case—depends not only on the emergent characteristics of the “collective,” but also on the resolution of challenges particular to organizational fields. Two very differently conceived lesbian and gay festival organizations, sites at which decision making about collective identity is ongoing and self-conscious, are examined. The analysis traces how each responds to two related tasks: maintaining community legitimacy, which requires racial diversification, and surviving within an altered institutional environment. Rather than imposition from “above” or construction from “below,” the adaptive responses by organizations (to changes in both community expectations and the resource environment) transform the collective identity formulations reaching public visibility. Earlier versions of this paper were presented at the Colloquium Series of the Center for Lesbian and Gay Studies, City University of New York, 1995, and at the Annual Meeting of the American Sociological Association, Washington, DC, 1995.     

Low dose risk estimation via simultaneous statistical inferences

Summary.  The paper develops and studies simultaneous confidence bounds that are useful for making low dose inferences in quantitative risk analysis. Application is intended for risk assessment studies where human, animal or ecological data are used to set safe low dose levels of a toxic agent, but where study information is limited to high dose levels of the agent. Methods are derived for estimating simultaneous, one-sided, upper confidence limits on risk for end points measured on a continuous scale. From the simultaneous confidence bounds, lower confidence limits on the dose that is associated with a particular risk (often referred to as a bench-mark dose ) are calculated. An important feature of the simultaneous construction is that any inferences that are based on inverting the simultaneous confidence bounds apply automatically to inverse bounds on the bench-mark dose.     

Benchmark Analysis: Shopping with Proper Confidence

We discuss the issue of using benchmark doses for quantifying (excess) risk associated with exposure to environmental hazards. The paradigm of low-dose risk estimation in dose-response modeling is used as the primary application scenario. Emphasis is placed on making simultaneous inferences on benchmark doses when data are in the form of proportions, although the concepts translate easily to other forms of outcome data.     

Scissors, Surveys, And Psycho-Prophylactics: Prenatal Health Care Campaigns And State Building In China, 1949–1954

This paper examines how the Chinese state's prenatal health care campaigns of the early 1950s attempted to redefine women's social and political roles. The replacement of local midwifing practices with a uniform birthing method in order to radically reduce infant and mother mortality entailed complex ramifications regarding the relationship of women vis-a-vis the state. Campaigns involved demonizing "traditional" midwifing, promoting a statistical vision of female reproductivity and children as national resources, and the isolation of individual mothers as directly responsible to the state for managing reproduction for the national interest. In sum, a physiological definition of gender was used to open women's bodies to state management. Utopic visions of painless childbirth and of the socialist nation as a giant new family were used to promote participation in grassroots campaigns, but the sources also point to forms of local resistance to the micro-level reorganization of power these campaigns intended.     

Population structure and correlation between auxiliary and target variables may affect precision of estimates in forest inventory

Simulations of forest inventory in several populations compared simple random with “quick probability proportional to size” (QPPS) sampling. The latter may be applied in the absence of a list sampling frame and/or prior measurement of the auxiliary variable. The correlation between the auxiliary and target variables required to render QPPS sampling more efficient than simple random sampling varied over the range 0.3–0.6 and was lower when sampling from populations that were skewed to the right. Two possible analytical estimators of the standard error of the estimate of the mean for QPPS sampling were found to be less reliable than bootstrapping.