Philippine migration policy: dilemmas of a crisis

Philippine migration policy is traced from the early 1970s to the present. The main migration trends in the 1990s are described. An assessment is made of the efficacy and appropriateness of present migration policy in light of the economic crisis. A regional approach to migration policy is necessary in order to encourage placing migration as a greater priority on national agendas and in bilateral agreements. In the Philippines, migrants are considered better paid workers, which diminishes their importance as a legislative or program priority. Santo Tomas (1998) conducted an empirical assessment of migration policies in the Philippines, but refinement is needed. Although migration is a transnational experience, there is little dialogue and cooperation among countries. Philippine migration policy defines its role as an information resource for migrants. Policy shifted from labor export to migrant management in the public and private sectors. Predeparture information program studies are recommending a multi-stage process that would involve all appropriate parties. There is talk of including migration information in the education curriculum. There are a variety of agendas, competing interests, and information resources between migration networks and officiating agencies. The Asian financial crisis may have a mild impact, but there are still issues of reintegration, protection, and employment conditions     

The new management competencies: a global perspective

How will tighter controls over health expenditures, an increased supply of qualified doctors, and clinical acumen becoming more critical in allocating health resources under market-driven, capitated payment-type plans affect physicians? Throughout the world, they will play a greater role in the management of health facilities and services. To train doctors to provide leadership in these new, more market driven environments, education should focus more on the integration and coordination of clinical and managerial processes, an approach outside the scope of most curricula now offered. New managerial competencies will be required by the paradigm shift away from simply delivering quality health services to tighter cost containment efforts. Physicians will play an increasing role in how medical facilities and services are organized and financed--the blending of clinical and managerial-financial-information science processes will be paramount in these educational pursuits.     

The Impact of Sense of Community in the School,Social Skills,and Exposure to Aggression and Victimization on Students’ Well-Being

Research suggests that sense of community in the school is a promising construct in terms of its ability to promote students’ well-being. However, mechanisms behind and the potential benefits of school sense of community have not been studied in detail. This cross-sectional study tested a model which examined the role of sense of community in the school, social skills, exposure to aggression, and victimization in shaping students’ well-being. The sample consisted of 1076 students from 22 public middle schools and 724 students from 22 public high schools located in the Italian Region of Liguria. Using a Bayesian estimation for a structural equation model, results showed that sense of community in the school directly predicted students’ social skills, exposure to aggression, and well-being and, indirectly (through social skills and exposure to aggression), victimization. In addition, we found that social skills were related to victimization. Finally, results showed that victimization was predicted by exposure to aggression and predicted well-being. The current study suggests that sense of community in the school and social skills are key variables for interventions that aim to prevent aggressive behaviors at school and to increase students’ well-being.     

The residential landscape: fluxes of elements and the role of household decisions

We assessed biogeochemical cycling of elements through residential household landscapes to evaluate the importance of annual to decadal household-level decisions for element fluxes that contribute to urban and regional pollution. We combined a mailed survey, vegetation measurements, and allometric and biogeochemical models to estimate fluxes and accumulation of carbon (C), nitrogen (N), and phosphorus (P) in landscapes of 360 single-family homes in the Minneapolis-Saint Paul, Minnesota metropolitan area. Carbon inputs and accumulation were strongly influenced by the presence of trees on the property. Nitrogen inputs to the landscape exceeded estimated ecosystem demand for N on average by 51% and were dominated by N fertilizer application. Because Minnesota state law restricts the use of P fertilizer, pet waste was responsible for 84% of P inputs to the landscape. The results have implications for understanding sources of urban pollution and the potential flexibility (i.e., the potential for change) in household behaviors such as tree planting, fertilization, and pet waste management that contribute to such pollution.     

Some Faults of the Bayes Factor in Nonparametric Model Selection

We compare different Bayesian strategies for testing a parametric model versus a nonparametric alternative on the ground of their ability to solve the inconsistency problems arising when using the Bayes factor under certain conditions. A preliminary critical discussion of such an inconsistency is provided.     

A family of power‐divergence diagnostics for goodness‐of‐fit

The author extends to the Bayesian nonparametric context the multinomial goodness‐of‐fit tests due to Cressie & Read (1984). Her approach is suitable when the model of interest is a discrete distribution. She provides an explicit form for the tests, which are based on power‐divergence measures between a prior Dirichlet process that is highly concentrated around the model of interest and the corresponding posterior Dirichlet process. In addition to providing interesting special cases and useful approximations, she discusses calibration and the choice of test through examples.     

Finite mixtures of matrix normal distributions for classifying three-way data

Matrix-variate distributions represent a natural way for modeling random matrices. Realizations from random matrices are generated by the simultaneous observation of variables in different situations or locations, and are commonly arranged in three-way data structures. Among the matrix-variate distributions, the matrix normal density plays the same pivotal role as the multivariate normal distribution in the family of multivariate distributions. In this work we define and explore finite mixtures of matrix normals. An EM algorithm for the model estimation is developed and some useful properties are demonstrated. We finally show that the proposed mixture model can be a powerful tool for classifying three-way data both in supervised and unsupervised problems. A simulation study and some real examples are presented.     

An improved statistical test for historical linguistics

Historical linguistics needs procedures to evaluate the similarity between languages through the comparison of specific word lists drawn from the whole vocabulary. The main issue is to evaluate a fair threshold for the number of similar items beyond which it is sensible to reject the hypothesis of chance similarity. After a short review of papers dealing with that problem, in this paper an extension of those methods is proposed which exploits available data in a more efficient way. In particular, the exact distribution of the new test statistics is calculated and the power of the new procedure is compared with the power of the existing method.     

Finding Relevant Linear Manifolds in Classification by Gaussian Mixtures

In this article, we present a strategy for producing low-dimensional projections that maximally separate the classes in Gaussian Mixture Model classification. The most revealing linear manifolds are those along which the classes are maximally separable. Here we consider a particular probability product kernel as a measure of similarity or affinity between the class-conditional distributions. It takes an appealing closed analytical form in the case of Gaussian mixture components. The performance of the proposed strategy has been evaluated on real data.