Heterogeneity across immigrants in the Spanish labour

The purpose of this paper is to analyze the diferences that immigrants have in the Spanish labour market. Immigrants in Spain come from a diversity of continents (Africa, South America, Eastern Europe, Asia, etc.), and there are substantial diferences in characteristics not only among continents but also among countries in each continent. Using a quantile regression method of decomposition we estimate these diferences that are reflected in the labour market and in particular are mirrored in the wage, so some immigrants are more discriminated or segregated that others because they have less advantage. For example Argentineans and Peruvians have the same origin and culture but we can find diferences in the wage that they receive in the Spanish labor market, or for example Moroccans have a advantage with respect to the Rest of Africans, due to the geographical proximity to Spain. So when we study the pay gap and the gender pay gap we need to take into consideration the origin of immigrants. We also want to study how the integration of immigrants evolved across years, whether the wage gap that we find in the first episode of work between immigrants and natives disappears or continues to be present in the Spain labour market.

Kernel-PCA data integration with enhanced interpretability

Background Nowadays, combining the different sources of information to improve the biological knowledge available is a challenge in bioinformatics. One of the most powerful methods for integrating heterogeneous data types are kernel-based methods. Kernel-based data integration approaches consist of two basic steps: firstly the right kernel is chosen for each data set; secondly the kernels from the different data sources are combined to give a complete representation of the available data for a given statistical task. Results We analyze the integration of data from several sources of information using kernel PCA, from the point of view of reducing dimensionality. Moreover, we improve the interpretability of kernel PCA by adding to the plot the representation of the input variables that belong to any dataset. In particular, for each input variable or linear combination of input variables, we can represent the direction of maximum growth locally, which allows us to identify those samples with higher/lower values of the variables analyzed. Conclusions The integration of different datasets and the simultaneous representation of samples and variables together give us a better understanding of biological knowledge.

La objeción de la ignorancia pública

Las teorías deliberativas de la democracia han pasado de cuestionar en su totalidad los sistemas democráticos representativos y sus procedimientos de toma de decisiones a buscar su posibilidad de realización acomodándose a las instituciones liberales. Sin embargo, la deliberación democrática sigue suscitando oposición entre varios autores por varias razones, una de las cuales, especialmente conspicua, es la llamada objeción de la ignorancia pública, que afirma que el público por su ignorancia de los asuntos políticos está incapacitado para cumplir las exigentes requisitos que toda deliberación política presupone y por la que esta, a gran escala, deviene indeseable, cuando no imposible.