Increasing contraceptive use in Bangladesh: The role of demand and supply factors

This article analyzes the determinants of contraceptive use in Bangladesh, focusing on the roles of demand for additional children and of family planning service supply. Data from the Matlab Family Planning Health Services Project are used to examine the contributions of these factors to the difference in prevalence of modern contraceptive use between the project area and a control area served by the government family planning and health programs. Results of multivariate analysis deriving from the Easterlin synthesis framework show the importance of family planning supply factors in reducing psychic and resource costs of fertility regulation and in activating latent demand for contraception. Demand for birth limiting and for birth spacing emerge as important explanatory factors; demand for birth spacing is greater in the project area, and both demand measures exert a stronger effect on contraceptive behavior in that area.     

The Influence of the Socio-economic Characteristics of Disabled People on Their Employment Status and Income

Most of the studies of the employment and income levels of disabled people focus on a specific disability or on severely disabled persons. A few studies are cross disability ones, but they fail to go beyond simple associations or else have extremely small sample sizes. There is a need for studies which are cross disability and which have an adequate sample size in order to determine if there are structural variables in society—like a class system-which operate upon the employment opportunities of disabled persons. Using a sample (n = 733) of the Disability Community in Massachusetts, socio-economic variables related to employment and income are studied. Statistically significant relationships are found. Several models are developed and the implications for social theory are discussed.     

Arrow's paradox and mathematical theory of democracy

Two measures, the weight of coalitions and the probability of situations in decision making, are used to characterize the representativeness, i.e. the capability of individuals to represent the social preference. It is proved that there always exists an individual who represents a majority on average, and an individual who represents a majority in most cases. This result is applied to Arrow's social choice model. It follows that there always exists a dictator who is a representative of the society rather than a dictator in a proper sense. After the concept of dictator has been refined to a dictator in a proper sense, Arrow's axioms become consistent. The idea of optimal representation is extended to limited groups of representatives which make decisions on behalf of the whole society. We consider the cabinet (named by analogy with the cabinet of ministers) which consists of a few representatives with delimited domains of competence, and the council which makes decisions by means of voting. It is shown that the representativeness of optimal cabinets and councils tends to 100% of maximally possible values as the number of their members increases, independently of the size of the society. We suggest a geometric interpretation of optimal representatives, cabinets, and councils, based on approximation formulas for the indicators of representativeness derived for the model with a large number of independent individuals. Finally, for cabinets and councils we establish the consistency of different concepts of optimality with respect to different indicators of representativeness. Our consideration is applicable to multicriteria decision making. An appointment of a cabinet or a council corresponds to selecting a few partial criteria. Therefore, the obtained results can be used for reducing the set of partial criteria to a certain sufficient minimum. The concepts of dictator, cabinet, and council can be understood as models of president, government, and parliament, respectively. Thus our results justify reducing social choice to individual choice or small group choice. Although it is in use in all democratic systems, its acceptability is not evident at all. In other words, we justify the demoncraticity of such forms of political power as the president, the parliament, and the government.     

Naming Men as Men: Implications for Work,Organization and Management

This paper seeks to contribute to the growing interest in naming men as men as part of a critical analysis of gendered power relations in organizations. The paper highlights the way in which men and masculinities are frequently central to organizational analysis, yet rarely the focus of interrogation. They remain taken for granted and hidden. Examining recent studies that contribute to a critical analysis of gendered power relations, we consider the growing interest in multiplicity, diversity and difference. In particular, we explore the issue of ‘multiple masculinities’ as well as some of the conceptual difficulties that surround it. Arguing for an approach which addresses the unities, differences and interrelations between men and masculinities, we suggest that critical studies of gendered power need to examine the management of organizations in much more detail. Highlighting five masculinities that seem to be routinely embedded in managerial discourses and practices, we conclude by advocating further research in this previously neglected area.     

Sampling Strategies for Toxic Air Contaminants

Annual concentrations of toxic air contaminants are of primary concern from the perspective of chronic human exposure assessment and risk analysis. Despite recent advances in air quality monitoring technology, resource and technical constraints often impose limitations on the availability of a sufficient number of ambient concentration measurements for performing environmental risk analysis. Therefore, sample size limitations, representativeness of data, and uncertainties in the estimated annual mean concentration must be examined before performing quantitative risk analysis. In this paper, we discuss several factors that need to be considered in designing field-sampling programs for toxic air contaminants and in verifying compliance with environmental regulations. Specifically, we examine the behavior of SO2, TSP, and CO data as surrogates for toxic air contaminants and as examples of point source, area source, and line source-dominated pollutants, respectively, from the standpoint of sampling design. We demonstrate the use of bootstrap resampling method and normal theory in estimating the annual mean concentration and its 95% confidence bounds from limited sampling data, and illustrate the application of operating characteristic (OC) curves to determine optimum sample size and other sampling strategies. We also outline a statistical procedure, based on a one-sided t-test, that utilizes the sampled concentration data for evaluating whether a sampling site is compliance with relevant ambient guideline concentrations for toxic air contaminants.     

TEACHING TOOLS: ECONOMICS OF CHILDHOOD IMMUNIZATION

Recent outbreaks of measles and other childhood diseases have put immunization policy on the national agenda. This teaching note on childhood immunization, intended for principles courses, discusses the rationale for government involvement, the situation in the U.S., and the policies of Northern Ireland and Austria. It emphasizes (a) the use of financial incentives to motivate behavior, (b) the distinction between shifting and moving along the demand curve, and (c) the notion of negative prices (i.e., paying the customer to "buy" the item). Students especially like the idea of the demand curve extending below the x-axis.     

Grounded Neural Networking: Modeling Complex Quantitative Data

The latest advances in artificial intelligence software (neural networking) have finally made it possible for qualitative researchers to apply the grounded theory method to the study of complex quantitative databases in a manner consistent with the postpositivistic, neopragmatic assumptions of most symbolic interactionists. The strength of neural networking for the study of quantitative data is twofold: it blurs the boundaries between qualitative and quantitative analysis, and it allows grounded theorists to embrace the complexity of quantitative data. The specific technique most useful to grounded theory is the Self‐Organizing Map (SOM). To demonstrate the utility of the SOM we (1) provide a brief review of grounded theory, focusing on how it was originally intended as a comparative method applicable to both quantitative and qualitative data; (2) examine how the SOM is compatible with the traditional techniques of grounded theory; and (3) demonstrate how the SOM assists grounded theory by applying it to an example based on our research.