Social Psychological and Structural Influences on Vegetarian Beliefs

Abstract This study examines the link between social structural variables (gender, race, education, age, rural childhood), individual social psychology (altruism, self-interest, traditionality, and openness to change), and beliefs about the benefits of vegetarianism (for health, the environment, animals, and world hunger) and self-reported vegetarianism. Data from a random sample of 420 adult U.S. residents showed that 5.2 percent considered themselves vegetarian. The strongest predictor of vegetarianism as a dietary choice was the belief that vegetarianism is beneficial to the environment. None of the social structural variables had a direct influence on vegetarianism as a dietary choice. Of the four values studied, only altruism and traditional values influenced beliefs about the benefits of vegetarianism. Altruistic values increased, and traditional values decreased, beliefs that vegetarianism is beneficial to health, the environment, farm animals, and world hunger. Blacks were more likely than Whites to adhere to the beliefs that vegetarianism helps prevent cruelty to farm animals, is beneficial to personal health, and is beneficial to the environment. The race differences in beliefs persisted even with controls for values.     

Mixture models for capture-recapture count data

The contribution investigates the problem of estimating the size of a population, also known as the missing cases problem. Suppose a registration system is targeting to identify all cases having a certain characteristic such as a specific disease (cancer, heart disease, ...), disease related condition (HIV, heroin use, ...) or a specific behavior (driving a car without license). Every case in such a registration system has a certain notification history in that it might have been identified several times (at least once) which can be understood as a particular capture-recapture situation. Typically, cases are left out which have never been listed at any occasion, and it is this frequency one wants to estimate. In this paper modelling is concentrating on the counting distribution, e.g. the distribution of the variable that counts how often a given case has been identified by the registration system. Besides very simple models like the binomial or Poisson distribution, finite (nonparametric) mixtures of these are considered providing rather flexible modelling tools. Estimation is done using maximum likelihood by means of the EM algorithm. A case study on heroin users in Bangkok in the year 2001 is completing the contribution.     

Analysis of longitudinal data using a finite mixture model

This paper considers a finite mixture model for longitudinal data, which can be used to study the dependency of the shape of the respective follow-up curves on treatments or other influential factors and to classify these curves. An EM-algorithm to achieve the ml-estimate of the model is given. The potencies of the model are demonstrated using data of a clinical trial.     

The Jewish Emigration from the Former Soviet Union to Germany

Since the end of the 1980s a massive emigration of Jews from the former Soviet Union (FSU) can be observed. Israel and the United States were the most important receiving countries, followed by Germany, a comparatively new immigration destination for Jews from the successor states of the USSR. One of the reasons the German Government allowed the admission of Jews from post-Soviet states was the Jewish community's claim that this immigration might rejuvenate the German Jewish population in the longer run. Using an index of demographic aging (Billeter's J), the following article examines if this has actually happened. Findings suggest that immigration actually initiated a process of rejuvenation in the Jewish population in Germany. However, it was reversed during the end of the 1990s because of an unaffected low fertility.     

Theory and Method in Social Impact Assessment *

Social Impact Assessment (SIA) is a method of policy analysis that offers great potential for integrating scientific policy analysis into a democratic political process. This potential has not been realized in large part because there has been no theoretical framework to guide SIA. In this paper I propose such a framework, using Habermas’(1970) pragmatistic approach to policy. The framework suggests heavy emphasis on use of SIA early in the policy process and on methods that emphasize impact identification and portrayal.     

Setting priorities in aging populations: formal service use among Mexican American female elders

This study establishes empirical patterns of formal service use by a sample of 483 elderly Mexican American women, and identifies the predictors of formal service utilization. Results indicated two patterns of service use-in the home and at senior centers. Regression analysis demonstrated that the best predictors of who used formal in-home services were those with functional impairment in Instrumental Activities of Daily Living (IADLs) and those with the least amount of assistance with IADLs provided by family members. Living alone and attending group social events were the best predictors of the use of senior center services. Anticipated changes in the Mexican American population portend a growing need for both in-home and senior center services. These findings can be used to establish policy and programming priorities for this neglected population. If resources are to be effectively targeted to frail elders, in-home services should receive priority, and the provision of in-home services should be modified to include additional programs that facilitate care of the elderly by the family.     

Practical scheduling for call center operations

A practical spreadsheet-based scheduling method is developed to determine the optimal allocation of service agents to candidate tour types and start times in an inbound call center. A stationary Markovian queueing model with customer abandonment is employed to determine required staffing levels for a sequence of time intervals with varying call volumes, handling times, and relative agent availabilities. These staffing requirements populate a quadratic programming model for determining the distribution of agent tours that will maximize the fraction of offered calls beginning service within a target response time, subject to side constraints on tour type quantities. The optimal distribution is scaled to reflect the total number of scheduled agents, and a near-optimal integer solution is derived using rounding thresholds found by successive one-dimensional searches. This novel approach has been successfully implemented in large service centers at Qwest Communications and could easily be adapted to other operational environments.     

The regulatory breadth index: A new tool for the measurement and comparison of state-level charity regulation in the United States

The bulk of charity regulation in the United States occurs at the state level, yet state-level charity regulation remains relatively under-researched within nonprofit scholarship, particularly from a comparative perspective. The complexity and variation in statutory regulation, coupled with the large volume of legal research required to study state-level charity regulation systematically, has impeded scholarly progress toward a better understanding of the US charitable sector. We address this problem by deriving a state-level charity regulatory breadth index (RBI) that will enable nonprofit researchers to contextualize state-level charity research within a broader framework and to incorporate state-level regulation into analyses across states. Policymakers can also benefit from the ability to benchmark their regulatory regimes against their peers.