“Police,Public Safety,and Race‐Neutral Discourse”

In the final decades of the 20th century policing in America was refashioned in the public image of community policing. Race‐neutral discourses dominate public and professional support for community‐oriented policing philosophies. In the contemporary era of hyper‐incarceration a focus on ethnoracial divisions grounded in the sociology of peculiar institutions is essential for documenting transformations in how the municipal police services are legitimized. Here I analyze how the public discourses of law‐and‐order center on distortions of social fact and public safety. Today the criminalization of immigrants is the latest turn in public discourses shaping patterns of ethnoracial visions and divisions. The carceral breadth of the neoliberal penal state extends beyond social structure, repackaged as race‐neutral ideology across the public sphere.     

Extending the Barnard’s test to non-inferiority

In 1945, George Alfred Barnard presented an unconditional exact test to compare two independent proportions. Critical regions for this test, by construction accomplish the very useful property of being Barnard convex sets. Besides, there are empirical findings suggesting that Barnard’s test is the most generally powerful. For Barnard’s test, calculation of critical regions is complicated due that they are constructed in an iterative form until is obtained a test size, as close as possible to the nominal significance level and less than or equal to it. In this article we present an extension to non-inferiority of this very leading test. This extension was contructed for any dissimilarity measure and tables were constructed for the difference between proportions. Also we calculate the critical regions for this extended test for sample sizes less or equal than 30, nominal significance level 0.01, 0.025, 0.05, and 0.10 and for non-inferiority margins 0.05, 0.10, 0.15, and 0.20. Additionally, we computed test sizes for the mentioned configurations. To do this calculations, we have written a program in the R environment.     

Fast and robust estimators of variance components in the nested error model

Usual fitting methods for the nested error linear regression model are known to be very sensitive to the effect of even a single outlier. Robust approaches for the unbalanced nested error model with proved robustness and efficiency properties, such as M-estimators, are typically obtained through iterative algorithms. These algorithms are often computationally intensive and require robust estimates of the same parameters to start the algorithms, but so far no robust starting values have been proposed for this model. This paper proposes computationally fast robust estimators for the variance components under an unbalanced nested error model, based on a simple robustification of the fitting-of-constants method or Henderson method III. These estimators can be used as starting values for other iterative methods. Our simulations show that they are highly robust to various types of contamination of different magnitude.     

Evaluating positive leadership: pilot study on the psychometric properties of a reduced version of the Positive Leadership Assessment Scale / Evaluando el liderazgo positivo: estudio piloto de las propiedades psicométricas de una versión reducida del Positive Leadership Assessment Scale

Positive leadership is considered a fundamental factor which contributes significantly to the development of healthy organizations. Positive leadership has been address via other leadership models, primarily transformational and authentic leadership, with which some affinities have been established. Although there is a large body of literature on positive leadership, especially related to its practical aspects, the construct is not properly delimited and there are only a few relevant contributions on how to measure it. The purpose of this paper is to conduct a pilot study to examine the psychometric properties of a reduced version of the PLAS (Positive Leadership Assessment Scale). Results from a confirmatory factorial analysis show that a five-correlated factors model achieves a good fit with the empirical data (on a sample of Spanish students). Likewise, this study also offers a range of evidence of validity, showing a relationship with the constructs of both transformational and authentic leadership and engagement.     

Classification of Poverty Condition Using Natural Language Processing

Social Indicators Research - This work introduces a methodology to classify between poor and extremely poor people through Natural Language Processing. The approach serves as a baseline to...     

A Bayesian analysis of directional data using the projected normal distribution

This paper presents a Bayesian analysis of the projected normal distribution, which is a flexible and useful distribution for the analysis of directional data. We obtain samples from the posterior distribution using the Gibbs sampler after the introduction of suitably chosen latent variables. The procedure is illustrated using simulated data as well as a real data set previously analysed in the literature.     

Programa shortstop: a culturally focused juvenile intervention for Hispanic youth

Culturally sensitive juvenile delinquency and substance abuse interventions are relatively limited and unavailable to many first-time Hispanic juvenile offenders. The purpose of this study was to test the effectiveness of a culturally focused juvenile and substance abuse intervention program for first time Hispanic youth offenders. The intent of the program was to decrease juvenile recidivism and increase substance abuse resistance. Programa Shortstop is a family based intervention designed for Hispanic youth ages 9-17. The intervention was delivered to 352 youth and at least one parent/caregiver over the 5-year study period. For intervention youth, the results of the recidivism study (n = 321) indicated that 89% of youth participating in Programa Shortstop between 1995 to 1997 were not rearrested within one year of completing Programa Shortstop. Additionally, statistical paired t-test analysis found that the intervention model had a positive effect on legal knowledge and school related factors associated with substance abuse and delinquency. Parent participants demonstrated significant increases in knowledge related to substance abuse and the legal system.     

Temporal disaggregation and restricted forecasting of multiple population time series

This article presents some applications of time-series procedures to solve two typical problems that arise when analyzing demographic information in developing countries: (1) unavailability of annual time series of population growth rates (PGRs) and their corresponding population time series and (2) inappropriately defined population growth goals in official population programs. These problems are considered as situations that require combining information of population time series. Firstly, we suggest the use of temporal disaggregation techniques to combine census data with vital statistics information in order to estimate annual PGRs. Secondly, we apply multiple restricted forecasting to combine the official targets on future PGRs with the disaggregated series. Then, we propose a mechanism to evaluate the compatibility of the demographic goals with the annual data. We apply the aforementioned procedures to data of the Mexico City Metropolitan Zone divided by concentric rings and conclude that the targets established in the official program are not feasible. Hence, we derive future PGRs that are both in line with the official targets and with the historical demographic behavior. We conclude that growth population programs should be based on this kind of analysis to be supported empirically. So, through specialized multivariate time-series techniques, we propose to obtain first an optimal estimate of a disaggregate vector of population time series and then, produce restricted forecasts in agreement with some data-based population policies here derived.     

Income distribution,economic growth and European integration

In this paper I discuss recent theories on the relationship between growth and inequality, and ask whether the two move together or not. Output growth can be due to increases in physical capital, human capital, employment or the level of technology, and I argue that each of these represents a mechanism that relates our two variables of interest. The European integration process has represented a major policy change that has affected not only the opportunities for growth but also the constraints faced by national governments. We can then ask whether such integration has had an effect on inequality, and to what extent it has resulted in a conflict between productive efficiency and distributive considerations.