Race Differences in Sexual Behavior and Their Demographic Implications

Differences between blacks and whites in sexual behavior posited in Rushton's theory of r-K race differences were examined in the United States in an analysis of the annual surveys of the National Opinion Research Center for 1990–1996. This data set was analysed for black-white differences in numbers of sexual partners during the last 5 years and for frequency of sexual intercourse. The general pattern of the results was for blacks to report more sexual partners than whites and for black males to report greater frequency of sexual intercourse, consistent with Rushton's theory. This result has implications for the control of the AIDS epidemic and for the demographic transition among blacks.     

Axiomatic foundations for fairness-motivated preferences

Much work in social choice theory takes individual preferences as uninvestigated inputs into aggregation functions designed to reflect considerations of fairness. Advances in experimental and behavioural economics show that fairness can also be an important motivation in the preferences of individuals themselves. A proper characterisation of how fairness concerns enter such preferences can enrich the informational basis of many social choice exercises. This paper proposes axiomatic foundations for individual fairness-motivated preferences that cover most of the models developed to rationalise observed behaviour in experiments. These models fall into two classes: Outcome-based models, which see preferences as defined only over distributive outcomes, and context-dependent models, which allow rankings over distributive outcomes to change systematically with non-outcome factors. I accommodate outcome-based and context-sensitive fairness concerns by modelling fairness-motivated preferences as a reference-dependent preference structure. I first present a set of axioms and two theorems that generate commonly used outcome-based models as special cases. I then generalise the axiomatic basis to allow for reference-dependence, and derive a simple functional form in which the weight on each person’s payoff depends on a reference vector of how much each person deserves.     

Methodological Approaches to Assessing Risk Perceptions Associated with Food-Related Hazards

The psychometric approach developed by Slovic and his co-workers has been effectively used to assess risk perceptions associated with different food-related hazards. However, further examination (using questionnaire data and partial correlation techniques) has indicated that technological hazards are highly differentiated from lifestyle hazards, in terms of both hazard control and knowledge about the hazard. Optimistic bias was also seen to vary between hazards. Further research has focused on a particular hazard, genetic engineering. Risk perceptions associated with genetic engineering are underpinned by ethical concern and questions relating to perceived need for the technology, as well as perceptions of risk or harm. However, increasing the specificity of hazard stimuli was found to alter the factor structure of underlying risk perceptions. The utility of preference mapping procedures in determining individual differences in trust in risk regulators is also discussed.     

Child care outcomes: economic perspectives and issues

Economics starts with the observation of widespread scarcity and the consequent need for choices about resource allocation. Common criteria for such choices are economy, effectiveness, efficiency and equity. This paper defines these criteria and locates them within a conceptual framework (the ‘production of welfare’). It also examines some of the reasons for the growth in interest in them. The main modes of evaluation—cost-benefit, cost-effectiveness, cost-utility and cost-consequences analyses—are described and illustrated. Few such evaluations have been conducted in child care, and the paper ends with speculation as to why this is so.     

Land-Grant University-Industry Relationships in Biotechnology: A Comparison with the Non-Land-Grant Research Universities1

Abstract The results of a 1986 survey of 185 biotechnology faculty in the land-grant colleges of agriculture are presented. Comparisons are made to a previous survey of biotechnology faculty in nonagricultural research universities. The survey investigates issues raised by industrial involvement in university biotechnology research and the impact of the new biosciences on the agricultural colleges. It was found that college of agriculture biotechnologists have more recently received their highest degrees, show more industrial involvement, and are more positive about the possible benefits of that involvement than their nonagricultural university counterparts. Industrial funding proved to be a significant exogenous variable affecting the activities and attitudes of agricultural college biotechnology faculty. Those with higher levels of industrial funding appear to have lower university productivity.     

Communicating Risks and Benefits from Fish Consumption: Impact on Belgian Consumers' Perception and Intention to Eat Fish

Communicating about the health effects of fish and seafood may potentially result in a conflict situation: increasing intake is desirable because of health and nutritional benefits, but higher consumption may also lead to an increased intake of potentially harmful environmental contaminants. In order to anticipate the communication challenge this conflict may pose, the research presented here aimed to assess the impact of risk/benefit communication on Belgian consumers' fish consumption behavior and fish attribute perception. Data were collected in June 2005 from a sample of 381 women, aged between 20 and 50 years. An experimental design consisting of four message conditions (benefit‐only; risk‐only; benefit‐risk; and risk‐benefit) combined with three information sources (fish and food industry; consumer organization; government) was used. Exposure to the benefit‐only message resulted in an increase from a self‐reported fish consumption frequency of 4.2 times per month to an intended fish consumption frequency of 5.1 times per month (+21%), while fish attribute perceptions only marginally improved. The risk‐only message resulted in a strong negative perceptual change in the range of two points on a seven‐point scale. This translated into an 8% decrease of behavioral intention (from eating fish 4.5 times per month to an intention of eating fish 4.1 times per month). Balanced messages referring to both risks and benefits yielded no significant change in behavioral intention, despite a significant worsening of fish attribute perception. The presentation order of benefits and risks in the balanced message showed a tendency to affect both behavioral intention and attribute perception, with the first message component being most influential. Information source did not yield any significant impact either on behavioral intention or on attribute perceptions, independent of the message content. The results from this study provide valuable insights for future risk/benefit and balanced communication about seafood.     

Inference in hybrid Bayesian networks using dynamic discretization

We consider approximate inference in hybrid Bayesian Networks (BNs) and present a new iterative algorithm that efficiently combines dynamic discretization with robust propagation algorithms on junction trees. Our approach offers a significant extension to Bayesian Network theory and practice by offering a flexible way of modeling continuous nodes in BNs conditioned on complex configurations of evidence and intermixed with discrete nodes as both parents and children of continuous nodes. Our algorithm is implemented in a commercial Bayesian Network software package, AgenaRisk, which allows model construction and testing to be carried out easily. The results from the empirical trials clearly show how our software can deal effectively with different type of hybrid models containing elements of expert judgment as well as statistical inference. In particular, we show how the rapid convergence of the algorithm towards zones of high probability density, make robust inference analysis possible even in situations where, due to the lack of information in both prior and data, robust sampling becomes unfeasible.