NGOization,Foreign Funding,and the Nicaraguan Civil Society

A substantial section of nongovernmental organizations (NGOs) in the global South depend on foreign funds to conduct their operations. This paper explores how the availability of foreign funding affects their downward accountability, abilities to effect social change, and their relative influence in relation to traditional grassroots, membership-based organizations (GROs), which tend not to receive such funding. Drawing on a case study of Nicaragua, we challenge the notion that foreign funding of domestic NGOs leads to the evolution of civil society organizations, which have incentives and abilities to organize the marginalized sections of society in ways to effect social change in their interests. Instead, we find that foreign funding and corresponding professionalization of the NGO sector creates dualism among domestic civil society organizations. Foreign funding enhances the visibility and prestige of the “modern” NGO sector over traditional GROs. This has grave policy implications because foreign-funded NGOs tend to be more accountable to donors than beneficiaries and are more focused on service delivery than social change-oriented advocacy.     

STOCHASTIC DOMINANCE AS A RISK ANALYSIS CRITERION*

This paper discusses the Stochastic Dominance (SD) approach to the evaluation of risky assets. Given a set of portfolios, the familiar EV procedure chooses a set of EV-efficient portfolios while the SD procedures choose SD-efficient sets that usually are quite similar to (but not identical with) the EV-efficient set. The SD approach can be employed as a refinement of the EV model or as an alternative method of evaluating portfolios. The SD view has certain conceptual advantages in the screening of a set of portfolios, but the EV model has the important advantage of an optimizing algorithm that builds efficient portfolios. Also, the SD approach requires more data than the EV approach.     

From Mirroring to World‐Making: Research as Future Forming

After decades of acrimonious debate on the nature of scientific knowledge, researchers in the human or social sciences are reaching a state of relative equanimity, a condition that may be characterized as a reflective pragmatism. Yet, even while the context has favored the development of new forms of research, the longstanding ocular metaphor of inquiry remains pervasive. That is, researchers continue the practice of observing what is the case, with the intent to illuminate, understand, report on, or furnish insight into given states of affairs. And, while selectively useful, such an orientation is not only limited in potential but subject to a receding span of application. As I will propose, when the logics of reflective pragmatism are fully extended, we enter a new territory of understanding, one in which the vision of research is radically altered. We replace the captivating gaze on the world as it is with value based explorations into what it could be. This conception of a future forming orientation to research opens the way to new aims, practices, and reflections.     

The Public's Changing Perceptions of the Condition of Social Welfare in Hong Kong: Lessons for Social Development

In the aftermath of the Asian financial crisis, the Hong Kong government introduced welfare reforms to ease the pressure from fiscal challenges and swelling welfare rolls; at the same time, to maintain its development credentials, it made an effort to adhere to its colonial tradition on the provision of welfare. The government adopted various strategies to garner popular support for promoting economic development as the primary goal and for promoting social harmony under the concept of ‘helping people to help themselves’. This article examines Hong Kong people's changing perceptions of the condition of social welfare in the past decade. Using a multidimensional developmental welfare approach and data from two opinion surveys conducted in 1997 and 2008, the study finds that Hong Kong people expressed a relatively high level of satisfaction about their own lives, but varying degrees of reservation about the problem of poverty, government provision of social welfare, and opportunities for social mobility. As a result of the sectorally unbalanced welfare reforms, which are biased against the disadvantaged, some of these perceptions have become more negative in recent years. Socially vulnerable people, especially the lower classes, are now more critical of the condition of social welfare, and such feelings seem to be intensifying. It is thus suggested that special attention to the issue of class should be paid in social development programmes to ensure social equality and social justice.     

Long-term solution to malpractice crises: reduce harm to patients

Physician executives need to lead the charge and actually reduce harm to patients. Simply capping malpractice awards or changing the rules of litigation is not enough.     

Children in Poverty: Do State Policies Matter?

Objective . Variations in childhood poverty are primarily responsive to changes in family structure and economic conditions. Some research also suggests that federal and state programs may help alleviate poverty among children. This research incorporates measures of family characteristics, economic conditions, and policy variables in estimating changes in childhood poverty among the U.S. states. Methods . The research design is a pooled time series for all 50 states for the years 1987–1996. Results . Economic and family circumstances indeed are the major forces affecting children in poverty among the states. The unemployment rate for females, the percentage births to unmarried mothers, and the percentage of single-parent families are especially useful estimators. Public policies are important as well: the state or federal minimum wage, Aid to Families with Dependent Children/food stamp payments, the Earned Income Tax Credit, and two measures of state child support effort. Conclusions . Although at times controversial, actions by the states and federal government can help reduce childhood poverty among U.S. states.     

An Ecological Regional Analysis of South Carolina

This study of the counties of South Carolina introduces a limited purpose, modifiable technology that is designed to reproduce the rapid discovery strategy of the natural sciences. It uses factor analysis to identify types of communities and the threats they face, and evaluates their success in dealing with these by comparisons based on age-adjusted mortality rates. The factor analysis of mostly census indicators generated an Urbanization factor along with two measures of the interaction with the environment, Growth and Poverty. Growth was expected to predict mortality negatively while Poverty should predict positively. Regression analysis confirms both predictions but only for each race. That is, Growth predicted lower mortality, but only for African-Americans. Poverty predicted higher mortality, but only for whites. These and other puzzling findings are explored, illustrating the “rapid discovery” technology that is the central feature of this paper.     

Aggregate male and female labor force participation functions: An analysis of structural differences, 1947–1977

The hypothesis that the structure of the forces that affect male and female labor force participation rates are distinct has been corroborated in numerous studies using microdata. This paper examines the validity of this structural distinctiveness hypothesis in the context of aggregate, time series data on male and female labor force participation in the post-World War II United States. Standard economic and sociological theories are used to specify sex-specific participation functions that contain indexes of the sex-specific general opportunity for employment, the sex-specific rates of participation in the armed forces and in postsecondary schooling institutions, the average real wage rate, the average number of hours worked, and the fertility rate. It is found that the female rate is more responsive than the male rate to the general employment opportunities and average hours indexes, but less responsive to the wage rate. Also, the female rate responds positively to the armed forces participation and college enrollment rates, whereas the male rate is negatively related to these indexes. However, no evidence is found for another component of the structural distinctiveness hypothesis, namely, that the fertility rate bears a consistent negative relationship to the female participation rate. While this relationship may have held during the early postwar years, it seems to have been substantially attentuated since the early 1960s. Prospects for convergence of the male and female participation functions are evaluated. Although current social trends suggest that the female function eventually will resemble more closely the male funtion, it is concluded that substantial sex differences are likely to persist for at least another decade. Implications of this for the structure of the labor force participation functions used in macroeconometric forecasting models are discussed.     

Linear latent structure analysis: Mixture distribution models with linear constraints

A new method for analyzing high-dimensional categorical data, Linear Latent Structure (LLS) analysis, is presented. LLS models belong to the family of latent structure models, which are mixture distribution models constrained to satisfy the local independence assumption. LLS analysis explicitly considers a family of mixed distributions as a linear space, and LLS models are obtained by imposing linear constraints on the mixing distribution.LLS models are identifiable under modest conditions and are consistently estimable. A remarkable feature of LLS analysis is the existence of a high-performance numerical algorithm, which reduces parameter estimation to a sequence of linear algebra problems. Simulation experiments with a prototype of the algorithm demonstrated a good quality of restoration of model parameters.     

Bootstrapping Regression Parameters in Multivariate Survival Analysis

Bootstrap methods are proposed for estimating sampling distributions and associated statistics for regression parameters in multivariate survival data. We use an Independence Working Model (IWM) approach, fitting margins independently, to obtain consistent estimates of the parameters in the marginal models. Resampling procedures, however, are applied to an appropriate joint distribution to estimate covariance matrices, make bias corrections, and construct confidence intervals. The proposed methods allow for fixed or random explanatory variables, the latter case using extensions of existing resampling schemes (Loughin,1995), and they permit the possibility of random censoring. An application is shown for the viral positivity time data previously analyzed by Wei, Lin, and Weissfeld (1989). A simulation study of small-sample properties shows that the proposed bootstrap procedures provide substantial improvements in variance estimation over the robust variance estimator commonly used with the IWM. This revised version was published online in July 2006 with corrections to the Cover Date.