Alcohol use among college students: responses to raising the purchase age

On December 1, 1985, New York State raised its alcohol purchase age from 19 to 21. We used a quasi-experimental research design to explore the changes in alcohol use behaviors and attitudes of undergraduates at a large central New York university before and after this legislation was enacted. The overwhelming majority of this undergraduate population is under 21 years old and is thus affected by the new legislation. A comparison of data from the two survey times revealed that 90% of the undergraduates sampled continued to drink at least occasionally. Our analysis of drinking quantity showed a slight moderation in alcohol consumption overall, with the greatest changes occurring for the heaviest drinkers--men and members of Greek organizations. Even with apparent moderation in student drinking, reported negative consequences such as physical injuries were more common. A change in drinking location to less-controlled environments, such as private rooms and unmonitored parties, is offered as one possible explanation.     

Estimating the Concentration of Propagules of a Plant Pathogen from Soil Dilution Plate Counts when the Response is Non-linear

The estimation of micro-organism concentrations from dilution plate data is discussed for situations where expected counts are not proportional to the amount of sample per plate. Aspects of design and analysis are investigated in relation to an alternative non-linear model in which the concentration is given by the slope at the origin. This exponential model generally provides a good fit to available experimental data. Simulations show that estimators based on the model perform well when the response is non-linear and remain reasonably efficient when the response is linear.     

A structural approach to women's hometime and experience-earnings profiles: Maternity leave and public policy

The differential availability of maternity leave benefits is shown to be an important factor in the earnings attainment process of women. Interaction effects with this job characteristic are found for experience, occupational status, and crowding. The human capital model's explanation of the relationship between women's hometime, women's job choice, and public policy is critically examined. The results indicate that the provision of adequate child care needs to be coupled with parental leave policies if women are to make significant gains in earnings from reducing their time spent at home.The data and tabulations used in this study were made available by the Inter-University Consortium for Political and Social Research. The data were originally collected by Robert P. Quinn and Graham L. Staines. Neither they nor the Consortium bear any responsibility for the analysis or interpretations presented here. This paper was presented at the 1989 American Sociological Association meetings.     

A common open space or a digital divide? A social model perspective on the online disability community in China

This paper explores the use and impact of the Internet by disabled people in China, informed by the social model of disability. Based on survey data from 122 disabled individuals across 25 provinces in China, study findings suggest that there is an emerging digital divide in the use of Internet amongst the disability community in China. Internet users in our study do not appear to be representative of most disabled people in China. For the minority of disabled people who do have access to the Internet, however, its use can lead to significantly improved frequency and quality of social interaction. Study findings further suggest that the Internet significantly reduced existing social barriers in the physical and social environment for disabled people. Implications for future research, and strategies for increasing reducing the digital divide between the minority of Internet users and the majority of disabled people in China are discussed.     

Evaluation of trace evidence in the form of multivariate data

Summary.  The evaluation of measurements on characteristics of trace evidence found at a crime scene and on a suspect is an important part of forensic science. Five methods of assessment for the value of the evidence for multivariate data are described. Two are based on significance tests and three on the evaluation of likelihood ratios. The likelihood ratio which compares the probability of the measurements on the evidence assuming a common source for the crime scene and suspect evidence with the probability of the measurements on the evidence assuming different sources for the crime scene and suspect evidence is a well-documented measure of the value of the evidence. One of the likelihood ratio approaches transforms the data to a univariate projection based on the first principal component. The other two versions of the likelihood ratio for multivariate data account for correlation among the variables and for two levels of variation: that between sources and that within sources. One version assumes that between-source variability is modelled by a multivariate normal distribution; the other version models the variability with a multivariate kernel density estimate. Results are compared from the analysis of measurements on the elemental composition of glass.     

Consumer-Phase Salmonella enterica serovar Enteritidis Risk Assessment for Egg-Containing Food Products

We describe a one-dimensional probabilistic model of the role of domestic food handling behaviors on salmonellosis risk associated with the consumption of eggs and egg-containing foods. Six categories of egg-containing foods were defined based on the amount of egg contained in the food, whether eggs are pooled, and the degree of cooking practiced by consumers. We used bootstrap simulation to quantify uncertainty in risk estimates due to sampling error, and sensitivity analysis to identify key sources of variability and uncertainty in the model. Because of typical model characteristics such as nonlinearity, interaction between inputs, thresholds, and saturation points, Sobol's method, a novel sensitivity analysis approach, was used to identify key sources of variability. Based on the mean probability of illness, examples of foods from the food categories ranked from most to least risk of illness were: (1) home-made salad dressings/ice cream; (2) fried eggs/boiled eggs; (3) omelettes; and (4) baked foods/breads. For food categories that may include uncooked eggs (e.g., home-made salad dressings/ice cream), consumer handling conditions such as storage time and temperature after food preparation were the key sources of variability. In contrast, for food categories associated with undercooked eggs (e.g., fried/soft-boiled eggs), the initial level of Salmonella contamination and the log10 reduction due to cooking were the key sources of variability. Important sources of uncertainty varied with both the risk percentile and the food category under consideration. This work adds to previous risk assessments focused on egg production and storage practices, and provides a science-based approach to inform consumer risk communications regarding safe egg handling practices.     

SHORT REVIEWS

Books reviewed in this article: Paul Demeny and Geoffrey Mcnicoll (eds.), Encyclopedia of Population Barbara Ehrenreich and Arlie Russell Hochschild (eds.), Global Woman: Nannies, Maids, and Sex Workers in the New Economy Food and Agriculture Organization of the United Nations, World Agriculture: Towards 2015/2030: An FAO Perspective and Summary Report Jeanne X. Kasperson and Roger E. Kasperson, Global Environmental Risk Richard Lynn, Eugenics: A Reassessment Douglas W. Maynard, Hanneke Houtkoop‐Steenstra, Nora Gate Schaeffer, and Johannes van der Zouwen (eds.), Standardization and Tacit Knowledge: Interaction and Practice in the Survey Anthony M. Messina (ed.), West European Immigration and Immigrant Policy in the New Century     

Characteristics of U.S. cities with extreme (high or low) crime rates: Results of discriminant analyses of 1960, 1970, and 1980 data

Why do some cities have higher or lower crime rates than others? In this study we attempt to answer this fundamental question by identifying the theoretically motivated structural covariates which differentiate U.S. cities with extreme high and low crime rates. We apply discriminant function analysis across comprehensive samples of all U.S. cities with populations of greater than 25 000 in the periods 1960, 1970, and 1980 and then posit four question: are empirical findings from regression-based studies of city crime rates replicated in discriminant studies with extreme rates? Are the covariates that predict high or low crime rates unique to specific time periods? Which covariates are better able to discriminate high or low rates for specific crimes? And are specific covariates distinguishable in crime rate changes across time periods? Among our general findings, it appears that those cities with extreme high (low) crime rates tend to be the largest (smallest), most (least) economically deprived, and most (least) socially disintegrated. Associations with these latter two characteristics appear to have grown stronger over the past three census periods. The theoretical importance of these and other findings uncovered here are discussed and interpreted through Wilson's (1987) notion of concentration effects and social isolation which may have transformed inner-city areas in recent years.