Fast parallel $$\alpha $$-stable distribution function evaluation and parameter estimation using OpenCL in GPGPUs

\(\alpha \)-Stable distributions are a family of probability distributions found to be suitable to model many complex processes and phenomena in several research fields, such as medicine, physics, finance and networking, among others. However, the lack of closed expressions makes their evaluation analytically intractable, and alternative approaches are computationally expensive. Existing numerical programs are not fast enough for certain applications and do not make use of the parallel power of general purpose graphic processing units. In this paper, we develop novel parallel algorithms for the probability density function and cumulative distribution function—including a parallel Gauss–Kronrod quadrature—, quantile function, random number generator and maximum likelihood estimation of \(\alpha \)-stable distributions using OpenCL, achieving significant speedups and precision in all cases. Thanks to the use of OpenCL, we also evaluate the results of our library with different GPU architectures.     

Measuring stakeholder identification with nonprofit causes: the development and validation of the identification with social causes scale

Nonprofit organizations (NPOs) achieve desired outcomes by fostering organizational identification. However, little research has explored how identification with the cause or the recipients of support relates to identification with the NPO. This study developed the Identification with Social Causes Scale as a mechanism for distinguishing organizational identification from identification with a social group or cause. Data were collected using two groups: the homeless (n = 318) and HIV positive (n = 314) individuals. Exploratory factor analysis and multigroup confirmatory factor analysis yielded a 9-item scale measuring two dimensions: attachment and consubstantiality. Initial construct validity of the scale was established.     

Factors Preventing Gridlock in Chilean Couples’ Relationships Based on the Discourse of Couples Therapists and Highly Adjusted Couples

The term gridlock describes the occurrence of rigid patterns in couples’ conflict. This study aimed to describe strategies of conflict resolution and gridlock prevention from the perspectives of couples and couple therapists. Participants were couple therapists and highly adjusted couples scored by the dyadic adjustment scale (DAS), distributed according to traditional and non‐traditional position in life and duration of relationships. Conflict gridlock scenarios were used to create video stimulus that were presented to participants. A qualitative methodology was used to analyse couples’ and therapists’ commentaries on the scenarios. Results showed differences in preventing conflict gridlock among sub‐groups of couples. Long‐term traditional couples focused on loyalty to a common project and value sacrificing to a higher good; long‐term non‐traditional couples prioritised caring and validating the bond in the relationship. Short‐term traditional couples focused on mutual love and the relief of hurt while short‐term non‐traditional couples supported the value of equity.     

Institutions,inculcation, and black racial identity: pigmentocracy vs. the rule of hypodescent

This research paper investigates the effect political institutions have on black racial identity. In particular, I study individual inculcation in contexts where political institutions institutionalize either of two forms of racial social structures – a pigmentocracy (the Dominican Republic), or the rule of hypodescent (the US South), and the effect such inculcation has on black racial identity. I sampled 101 respondents from the Dominican Republic and 102 from the state of Mississippi, USA. Consistent with the basic assumptions of my hypotheses, respondents in the Dominican Republic study sites showed a weaker degree of identification with blackness vis-à-vis something ‘whiter’. Nevertheless, respondents in the Dominican Republic sites demonstrated a stronger identification with blackness than what most conventional observers would have anticipated. Respondents in the Mississippi study sites showed a stronger sense of identification with blackness. Surprisingly, however, Mississippi respondents demonstrated a larger degree of neutrality than expected in their belief of being of a mixed racial heritage rather than just a black African heritage.     

Weber’s theory of domination and post-communist capitalisms

Theory and Society - This article has four main objectives. First, it introduces the ideal types of domination of Weber. Contrary to the received wisdom, which knows only “three ideal...     

Paternal domination and the mafia state under post-communism

This review essay discusses Bálint Magyar’s most recent book, Stubborn Structures: Conceptualizing Post-communist Regimes (Budapest: CEU Press 2019). Bálint Magyar first published in Hungarian in 2015 (published in English by CEU Press in 2016) a path-breaking book on The Post-Communist Mafia State: The Case of Hungary. This was the first major attempt to move beyond political controversies and offer a systematic critique of post-communist states. The book also went beyond the usual accusation of “corruption.” Magyar’s key point is that—at least in Hungary—a mafia style of “upper-world” was created, with a “godfather” at the top of it and an “adopted family” below it. This fascinating idea was followed by edited books that included contribution by other scholars. The latest such book is Magyar’s Stubborn Structures: Conceptualizing Post-communist Regimes (CEU Press 2019), which includes articles applying the “mafia state theory” to a great variety of post-communist countries.

     

Predicting Public Corruption with Neural Networks: An Analysis of Spanish Provinces

We contend that corruption must be detected as soon as possible so that corrective and preventive measures may be taken. Thus, we develop an early warning system based on a neural network approach, specifically self-organizing maps, to predict public corruption based on economic and political factors. Unlike previous research, which is based on the perception of corruption, we use data on actual cases of corruption. We apply the model to Spanish provinces in which actual cases of corruption were reported by the media or went to court between 2000 and 2012. We find that the taxation of real estate, economic growth, the increase in real estate prices, the growing number of deposit institutions and non-financial firms, and the same political party remaining in power for long periods seem to induce public corruption. Our model provides different profiles of corruption risk depending on the economic conditions of a region conditional on the timing of the prediction. Our model also provides different time frameworks to predict corruption up to 3 years before cases are detected.