Measuring labour market segmentation for a comparative analysis among countries

This article raises one main question in a comparative analytical exercise between two countries in different continents, Spain and Argentina. To what extent does labour market segmentation generate similar dynamics of structuring of labour inequalities in two countries with different socio-economic contexts and social models, and which aspects are specific to each country? The article is the first an analytical work aimed at comparing European and Latin American countries from the theoretical perspective of labour market segmentation. We set two main objectives. The first was to construct an analysis model to study inequalities in the labour market in comparative terms between Europe and Latin America, taking as a reference Spain and Argentina. To this end, demand and supply variables were combined from an employment perspective. We sought to corroborate the general hypothesis that there is no single labour market that adjusts supply and demand, but that several segments can be expected to structure hierarchical positions in the labour market in line with specific labour supply profiles. We expected to obtain a high correspondence between the employment segments of the two countries, despite the contextual and socio-historical differences. The second objective was to propose a methodology to obtain two synthetic measures of labour market segmentation: first, a categorical measurement through a typology constructed from hierarchical positions and profiles using multivariate techniques (combining multiple correspondence factor analysis [MCA] and cluster analysis [CLA]); and second, a continuous measurement based on the results of factor analysis, resulting in a composite indicator of labour inequality.

     

Improved inference for MCP-Mod approach using time-to-event endpoints with small sample sizes

The Multiple Comparison Procedures with Modeling Techniques (MCP-Mod) framework has been recently approved by the U.S. Food, Administration, and European Medicines Agency as fit-for-purpose for phase II studies. Nonetheless, this approach relies on the asymptotic properties of Maximum Likelihood (ML) estimators, which might not be reasonable for small sample sizes. In this paper, we derived improved ML estimators and correction for their covariance matrices in the censored Weibull regression model based on the corrective and preventive approaches. We performed two simulation studies to evaluate ML and improved ML estimators with their covariance matrices in (i) a regression framework (ii) the Multiple Comparison Procedures with Modeling Techniques framework. We have shown that improved ML estimators are less biased than ML estimators yielding Wald-type statistics that controls type I error without loss of power in both frameworks. Therefore, we recommend the use of improved ML estimators in the MCP-Mod approach to control type I error at nominal value for sample sizes ranging from 5 to 25 subjects per dose.     

Obstacles invisibles et représentation des femmes aux postes de décision en Espagne

Les auteurs présentent les résultats d'une étude sur les caractéristiques personnelles et les qualifications d'hommes et de femmes assumant des fonctions de direction dans des entreprises espagnoles, leur situation professionnelle et leur point de vue sur l'égalité des sexes. Par rapport à leurs homologues masculins, les Espagnoles occupant des postes à responsabilités sont plus jeunes mais aussi qualifiées, voire plus, et elles ont moins d'enfants. Cependant, elles sont toujours confrontées à des obstacles qui empěchent la pleine exploitation d'un capital humain précieux. Malgré les mesures adoptées, plus de neuf postes de décision sur dix sont toujours occupés par des hommes.     

Making projects, making friends: online community as catalyst for interactive media creation

To become full and active participants in today's technologically saturated society, young people need to become creators (and not just consumers) of interactive media. Developing the requisite abilities and capacities is not a wholly individual process; it is important for young people to have access to communities where they can collaborate and share ideas. This article uses the Scratch online community for exploring how different forms of participation and collaboration can support and shape the ways in which young people develop as creators of interactive media. We describe participation in this community in terms of a spectrum ranging from socializing to creating and present examples of three forms of collaboration within the community. We argue that the most exciting interactive media creation and valuable learning experiences are taking place in the middle space, where participants draw on the best of socializing and creating practices.     

Violence against bisexuals, gays and lesbians in Mexico City

An essential premise of this work is that three dominant ideologies explain oppression against BGL, as a result of a gender system: adhesion to gender stereotypes, androcentrism and heterosexism. Three hundred eighteen bisexual and gay males (BG) and 188 bisexual and lesbian females (BL) were surveyed. By means of a self-applied questionnaire, variables of interest were researched. The following trends were observed: an important number of men and women interviewed suffered violence in their childhood and adolescence because they defied gender stereotypes, and not because of their sexual orientation; BG males were more often victims of violence than BL females. Within the BG group, those who challenged gender stereotypes were more frequently attacked than those who did not; men were identified as aggressors more frequently than women; and in the BG group, gender stereotype transgression was associated with the perception of suffering violence in the future.     

Subjective machines: Probabilistic risk assessment based on deep learning of soft information

For several years machine learning methods have been proposed for risk classification. While machine learning methods have also been used for failure diagnosis and condition monitoring, to the best of our knowledge, these methods have not been used for probabilistic risk assessment. Probabilistic risk assessment is a subjective process. The problem of how well machine learning methods can emulate expert judgments is challenging. Expert judgments are based on mental shortcuts, heuristics, which are susceptible to biases. This paper presents a process for developing natural language-based probabilistic risk assessment models, applying deep learning algorithms to emulate experts’ quantified risk estimates. This allows the risk analyst to obtain an a priori risk assessment when there is limited information in the form of text and numeric data. Universal sentence embedding (USE) with gradient boosting regression (GBR) trees trained over limited structured data presented the most promising results. When we apply these models’ outputs to generate survival distributions for autonomous systems’ likelihood of loss with distance, we observe that for open water and ice shelf operating environments, the differences between the survival distributions generated by the machine learning algorithm and those generated by the experts are not statistically significant.     

Voluntary childlessness in a society reluctant to change

Voluntary childlessness constitutes a social and generational rupture from tradition and culture, with significant effects on the reproduction of the so-called life and family cycle. This study aims at understanding the reasons why people decide to remain childless and the social pressures that this decision generates. A qualitative phenomenological study was conducted on the emerging decision of non-motherhood and non-fatherhood based on semi-structured interviews with 56 people who autonomously made the decision to opt out of parenthood. This paper underscores the multiple biographical situations involved in the decision, in addition to the concerns about personal development and future. The current social crisis context serves as a means of justification to lessen social and family pressure. We conclude that people who have made this decision promote a different meaning from that of reproduction as a mechanism of the social order.     

Putting experts in their place: Achieving policy impact as an outsider-academic in civil service reforms in Slovakia

This paper studies two processes of civil service reform in Slovakia during the period of 2014–2015 in order to reflect on the involvement of an ‘outsider-academic’ and her strategies to achieve policy impact. The context of such involvement are multi-level processes permeated by political interests and poor on evidence, which favour strategic interests, bargaining and political pressure and contestation (the mode of ‘powering’) and a mode of legal-based ‘puzzling’ as opposed to a conceptual, intellectual search for solutions friendly towards outside academics—and achieving only incremental results. We theorise on the success of these strategies (including helping serendipity, throwing ideas to see what sticks, mobilising allies, anchoring a non-binding concept, and finding and developing long-term connections) and sketch analogies and differences between the position of an outsider-academic and a policy entrepreneur. We rely on auto-ethnographic data and documentation of the work of the committees involved and their outputs.     

More than ideology: perceived unfairness differentiates supporters of a new anti-austerity party from supporters of traditional left-wing parties / Más que ideología: la injusticia percibida diferencia a los simpatizantes de un nuevo partido antiausteridad de los simpatizantes de los partidos tradicionales de izquierda

After the outbreak of the economic crisis in 2008, anti-austerity parties in South Europe have gained prominence and dramatically transformed the political landscape. In Spain, the emergence of PODEMOS, a left-wing, anti-austerity party, has jeopardized the traditional two-party system. However, little is known about the psychological reasons that prompted more than one million Spaniards to vote for a newly created party in its first elections. To fill this gap the present study examines why people intend to vote for PODEMOS as opposed to traditional left-wing parties. We found that in addition to conventional predictors of voting behaviour (ideological orientation and party identification), perceived unfairness — a key variable within the collective action theory — critically influenced the preference for PODEMOS as opposed to traditional left-wing parties. A qualitative analysis of the reasons that participants reported in an open question yielded similar results. These findings suggest that supporting an anti-austerity party might be considered a collective action aimed at promoting social change.