The city in the country: Growing alternative food networks in Metropolitan areas

Alternative food networks (AFNs) are commonly defined by attributes such as the spatial proximity between farmers and consumers, the existence of retail venues such as farmers markets, community supported agriculture (CSA) and a commitment to sustainable food production and consumption. Focusing upon processes rather than attributes, this paper identifies two place-based processes that both promote and constrain the emergence and development of AFNs. Urbanization and rural restructuring are critical to the development of AFNs. AFNs are not a “thing” to be described, but rather emerge from political, cultural and historical processes. The interactions of urbanization and rural restructuring produce AFNs that are differentiated and marked by uneven development that does not necessarily support all farmers participating in the network. This indicates both the fragility and the dynamism inherent in AFNs that are tied to metropolitan development and change. Paradoxically, increasing urban demand for seasonal, and organic produce grown ‘close to home’ and the processes of rural restructuring which emphasize small-scale sustainable family farming and its direct food linkages to cities do not necessarily enable all farmers to consistently make a living from season to season. Evidence for these claims comes from an in-depth, qualitative case study reliant upon participant observation, in-depth interviews and draws from a statewide farmer survey and a regional consumer survey in Washington State.     

ASYMPTOTIC LIKELIHOOD APPROXIMATIONS USING A PARTIAL LAPLACE APPROXIMATION

Elimination of a nuisance variable is often non‐trivial and may involve the evaluation of an intractable integral. One approach to evaluate these integrals is to use the Laplace approximation. This paper concentrates on a new approximation, called the partial Laplace approximation, that is useful when the integrand can be partitioned into two multiplicative disjoint functions. The technique is applied to the linear mixed model and shows that the approximate likelihood obtained can be partitioned to provide a conditional likelihood for the location parameters and a marginal likelihood for the scale parameters equivalent to restricted maximum likelihood (REML). Similarly, the partial Laplace approximation is applied to the t‐distribution to obtain an approximate REML for the scale parameter. A simulation study reveals that, in comparison to maximum likelihood, the scale parameter estimates of the t‐distribution obtained from the approximate REML show reduced bias.     

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.     

Effects of Risk and Time Preference and Expected Longevity on Demand for Medical Tests

Despite their conceptual importance, the effects of time preference, expected longevity, uncertainty, and risk aversion on behavior have not been analyzed empirically. We use data from the Health and Retirement Study (HRS) to assess the role of risk and time preference, expected longevity, and education on demand for three measures used for early detection of breast and cervical cancer—regular breast self-exams, mammograms, and Pap smears. We find that individuals with a higher life expectancy and lower time preference are more likely to undergo cancer screening. Less risk averse individuals tend to be more likely to undergo testing.     

An R2criterion based on optimal predictors

The predictor that minimizes mean-squared prediction error is used to derive a goodness-of-fit measure that offers an asymptotically valid model selection criterion for a wide variety of regression models. In particular, a new goodness-of-fit criterion (cr²) is proposed for censored or otherwise limited dependent variables. The new goodness-of-fit measure is then applied to the analysis of duration.     

Ecological Concern, Attitudes, and Social Norms in Voting Behavior

Using a theoretical framework not previously tested in environmentalresearch, this study investigates the indirect relationshipbetween ecological concern and voting behavior. Results indicatethat the effects of ecological concern are mediated by attitudinal,normative, and behavioral intention variables. The results alsoprovide a partial test of the validity of Ajzen and Fishbein'sTheory of Reasoned Action. Key environmental, public policy,and communications implications are discussed.     

Allocation of research and development funds: A zero-one goal programming approach

The research and development project selection process is one of the most difficult and important problems faced by management. It is typically complicated by indivisibility of projects and multiple and conflicting objectives, in addition to limitations on funding, facilities, and qualified researchers. In this paper a case example involving a high technology electrical equipment manufacturer is developed to illustrate this problem using zero—one goal programming to accommodate indivisibility of projects in addition to multiple and conflicting goals. The model presented is an attempt to provide managers with a robust tool for allocating scarce resources among research and development projects.