Operations research from the viewpoint of general systems theory

This paper examines the operations research process from the viewpoint of General Systems Theory. The components of the OR process and the relations between them are critically examined. The five components are: (1) the “reality” of the problem situation, (2) the conceptual model of the problem situation, (3) the scientific model of the conceptual model, (4) the solution to the scientific model, and (5) the implementation of the solution. The paper argues that we have sub-optimized both our knowledge (study) and our application of the OR process. That is, there have been extremely few studies and applications of OR which have concerned themselves with OR from a whole systems point of view. The paper argues that without a whole systems perspective OR can neither be understood nor effectively applied.     

Ethnic pride, biculturalism, and drug use norms of urban American Indian adolescents

This study examines how strength of ethnic identity, multiethnic identity, and other indicators of biculturalism relate to the drug use norms of urban American Indian middle school students. The article distinguishes categories of norms that may affect drug use. Regression analysis of self-reports by 434 American Indian seventh graders attending middle schools in a large southwestern U.S. city indicated that students who had a more intense sense of ethnic pride adhered more strongly to certain antidrug norms than those who did not. Whereas American Indian students with better grades in school held consistently stronger antidrug norms, there were few differences by gender, socioeconomic status, or age. These results have implications in social work practice for better understanding and strengthening the protective aspects of American Indian culture in drug prevention efforts.     

The Poisson–exponential distribution: a Bayesian approach

In this paper, we proposed a new two-parameter lifetime distribution with increasing failure rate. The new distribution arises on a latent complementary risk scenario. The properties of the proposed distribution are discussed, including a formal proof of its density function and an explicit algebraic formulae for its quantiles and survival and hazard functions. Also, we have discussed inference aspects of the model proposed via Bayesian inference by using Markov chain Monte Carlo simulation. A simulation study investigates the frequentist properties of the proposed estimators obtained under the assumptions of non-informative priors. Further, some discussions on models selection criteria are given. The developed methodology is illustrated on a real data set.     

Bayesian Estimation of the Log–linear Exponential Regression Model with Censorship and Collinearity

In this work, a simulation study is conducted to evaluate the performance of Bayesian estimators for the log–linear exponential regression model under different levels of censoring and degrees of collinearity for two covariates. The diffuse normal, independent Student-t and multivariate Student-t distributions are considered as prior distributions and to draw from the posterior distributions, the Metropolis algorithm is implemented. Also, the results are compared with the maximum likelihood estimators in terms of the mean squared error, coverages and length of the credibility and confidence intervals.     

The Effect of Rainfall on Migration from Mexico to the United States

There has been very little work on the impact of rainfall on migration from Mexico or even elsewhere. We use satellite data from NASA to examine the effect of the lagged level of rainfall relative to an area's historical average, on migration from small Mexican communities to the United States. Controlling for the level of education, proportion married, and historic migration levels, we find higher levels of rainfall significantly reduce Mexican migration to the United States and a 20 percentage point higher‐than‐normal level of rainfall leads to a predicted 10.3 percent decrease in migration.     

Re-Placing Objects

This essay contemplates the importance of things and places for psychoanalysis. In contrast to the more common psychoanalytic category of space, it celebrates the density and specificity of place. In contrast to relational and internal objects, it examines material objects, with a special emphasis on the materiality of the transitional object. Materiality, it proposes, is a reservoir of innovation.     

Challenging the neoliberal view of education: the Center for Ecoliteracy as a transformative educational practice

The neoliberal rationality of recent decades has, as one of its maxims, that of extending market logic to the rest of social dimensions on the basis of competition. However, the spreading of this neoliberal ‘drug’ requires profound political reforms. It calls for a cultural engineering of the public sector which has been fostered by the New Public Management (NPM). This form of governmentality controls current power relations and gives a new meaning to the management of public services, including the educational sector. In this paper, we maintain that there are ‘spaces of resistance’ against the neoliberal educational rationality. We analyse the Center for Ecoliteracy (CFE) as a transformative experience which integrates a holistic perspective into educational practice. We compare the principles of the NPM with those of the CFE, showing that there are more humanistic approaches to education which aim to teach students the need to live in sustainable communities.     

Simulation-based model comparison methodology with application to road accident models

This article assumes the goal of proposing a simulation-based theoretical model comparison methodology with application to two time series road accident models. The model comparison exercise helps to quantify the main differences and similarities between the two models and comprises of three main stages: (1) simulation of time series through a true model with predefined properties; (2) estimation of the alternative model using the simulated data; (3) sensitivity analysis to quantify the effect of changes in the true model parameters on alternative model parameter estimates through analysis of variance, ANOVA. The proposed methodology is applied to two time series road accident models: UCM (unobserved components model) and DRAG (Demand for Road Use, Accidents and their Severity). Assuming that the real data-generating process is the UCM, new datasets approximating the road accident data are generated, and DRAG models are estimated using the simulated data. Since these two methodologies are usually assumed to be equivalent, in a sense that both models accurately capture the true effects of the regressors, we are specifically addressing the modeling of the stochastic trend, through the alternative model. Stochastic trend is the time-varying component and is one of the crucial factors in time series road accident data. Theoretically, it can be easily modeled through UCM, given its modeling properties. However, properly capturing the effect of a non-stationary component such as stochastic trend in a stationary explanatory model such as DRAG is challenging. After obtaining the parameter estimates of the alternative model (DRAG), the estimates of both true and alternative models are compared and the differences are quantified through experimental design and ANOVA techniques. It is observed that the effects of the explanatory variables used in the UCM simulation are only partially captured by the respective DRAG coefficients. This a priori, could be due to multicollinearity but the results of both simulation of UCM data and estimating of DRAG models reveal that there is no significant static correlation among regressors. Moreover, in fact, using ANOVA, it is determined that this regression coefficient estimation bias is caused by the presence of the stochastic trend present in the simulated data. Thus, the results of the methodological development suggest that the stochastic component present in the data should be treated accordingly through a preliminary, exploratory data analysis.     

A Century of Nuptiality in Spain, 1900–2007

This article describes the annual evolution of nuptiality in Spain from the beginning of the last century up to the present day. The analysis is based on data on first marriages from population registration data (Movimiento Natural de Población) after various adjustment and estimation operations. This source has an advantage with respect to census data, since it allows us to follow the annual nuptiality fluctuations that are very sensitive to prevailing social and economic conditions. Over the long term, the phases of nuptiality in Spain are comparable to those observed in Western Europe. However, leaving aside the period disturbed by the Civil War (1936–1939), Spain does exhibit some particular features: a long interlude from 1940 to 1959 marked by late marriage, rooted in the long depression of the Spanish economy; a prolonged rise in nuptiality which lasted until the end of the 1970s, corresponding to the late arrival of the first oil shock in Spain; and finally, a certain delay in the decline of marriage, accompanied—since the early 2000s only—by a parallel diffusion of cohabitation. Last, Spain is converging with Europe in another aspect that is seldom taken into account. While, from 1950 to 1980, it was one of the few European countries to register a first marriage rate unfavourable to women, the reversal of this trend since the 1980s has brought Spain closer to the majority of its neighbours.