Criminal Law: 2007-2010 Survey of Florida Law

Pearl Goldman, Criminal Law: 2007-2010 Survey of Florida Law, 35 Nova Law Review 95 (2010)

Stimulating a Response: Does Exposure to the Confederate Flag Impact People’s Attitudes Regarding Social Dominance Orientation, Ethnocultural Empathy, and their Political Beliefs?

Minimal psychological research has looked at whether priming participants with the Confederate flag impacts psychological functioning. The current study examined whether Confederate flag priming and people’s political orientation would account for various indicators of how people reconcile in-group/out-group divisions- social dominance orientation (SDO) and ethnocultural empathy (EE). Previous research noted that exposing people to the Confederate flag activates schemas resulting in biased judgments of out-group members (Becker, Enders-Comber, Wagner, Christ, & Butz, 2012; Callahan & Ledgewood, 2016; Kemmelmeier & Winter, 2008). Other studies noted that exposure to the Confederate flag changed voter’s preferences for political candidates, such as Barack Obama due to the activation of negative feelings towards Blacks (Ehrlinger et al., 2011). The current study builds from such work by examining the political attitudes of 194 participants enrolled in a midsized, primarily minority-serving university in the southern United States. Participants were exposed to 30 seconds of either the Confederate flag or a control group condition (an Olympic flag). After the exposure, participants’ attitudes towards SDO and EE were reported. Findings indicated that political ideology interacted with the flag condition and that the disparities were most pronounced when people of a particular political orientation were exposed to the Confederate rather than Olympic flag condition. Specifically, when exposed to the Confederate flag conservatives reported more SDO (i.e., less endorsement of group equality) and less EE (e.g., empathic feelings). By contrast, for liberals EE empathic awareness subscale scores were especially higher in the Confederate flag condition. Multiple main effects also emerged in which liberals generally reported lower SDO and higher EE than conservatives did (regardless of the flag priming). Implications concerning the current political climate in the U. S. and information shortcuts for potential voting behavior are also discussed

Influence of maternal and social factors as predictors of low birth weight in Italy

Abstract Background The purpose of this study is to provide insight into the determinants of low birth weight (LBW) in Italy. Methods The study was carried out in a non-teaching hospital in Catanzaro (Italy). All LBW and very LBW newborns (200) were included in the study and a random sample of 400 newborns weighing ≥ 2500 g was selected. Data were collected from the delivery certificates during one year. Smoking activity of mother and familiar and/or social support during pregnancy was gathered through telephone interviews. Results Overall annual LBW rate was 11.8%. Among LBW newborn there were 125 preterm and 75 term. Younger mothers, those who smoked during pregnancy, and had fewer prenatal care visits were more likely to deliver a LBW child; moreover, preterm newborns, delivered by caesarean section, and twin or multiple birth were significantly more likely to have a LBW. The comparison of very LBW ( Conclusion Several modifiable factors affect the risk of LBW, even when universal access to health care is freely available, but socio-economic status appears to correlate only to very LBW.</p

The twilight of the Liberal Social Contract? On the Reception of Rawlsian Political Liberalism

This chapter discusses the Rawlsian project of public reason, or public justification-based 'political' liberalism, and its reception. After a brief philosophical rather than philological reconstruction of the project, the chapter revolves around a distinction between idealist and realist responses to it. Focusing on political liberalism’s critical reception illuminates an overarching question: was Rawls’s revival of a contractualist approach to liberal legitimacy a fruitful move for liberalism and/or the social contract tradition? The last section contains a largely negative answer to that question. Nonetheless the chapter's conclusion shows that the research programme of political liberalism provided and continues to provide illuminating insights into the limitations of liberal contractualism, especially under conditions of persistent and radical diversity. The programme is, however, less receptive to challenges to do with the relative decline of the power of modern states

Constitutivism

A brief explanation and overview of constitutivism

Philosophy of action

The philosophical study of human action begins with Plato and Aristotle. Their influence in late antiquity and the Middle Ages yielded sophisticated theories of action and motivation, notably in the works of Augustine and Aquinas.1 But the ideas that were dominant in 1945 have their roots in the early modern period, when advances in physics and mathematics reshaped philosophy

Desarrollo de un componente de analítica para la clasificación de textos cortos dirigido a un proyecto institucional e integrable en una plataforma Web

Auxiliar de InvestigaciónLa clasificación de texto es una de las áreas de estudio de la disciplina del aprendizaje de máquina (en inglés Machine Learning) en donde se busca, posterior a una etapa de entrenamiento, predecir una categoría para datos de entrada que no hayan sido clasificados previamente. La longitud de los textos cortos, puede conllevar a una pérdida en la precisión de los resultados entregados por el proceso de clasificación de texto, ya que la cantidad de características aprovechables disminuye. Por lo tanto, se busca explorar una solución que permita realizar tareas de clasificación de textos cortos, con un nivel de precisión cercano al 80 %. Se desarrolló un componente de clasificación de textos cortos en el lenguaje de programación Python, haciendo uso del framework Flask el cual permite peticiones a través de un API y realiza la clasificación datasets que cumplan con el formato de entrada. Se probaron los resultados de este trabajo mediante el uso de publicaciones extraídas desde cuentas de Twitter, debido a la restricción sobre la longitud de sus publicaciones. La clasificación se realizó mediante el uso de algoritmos de aprendizaje supervisado, y en el mejor de los casos, la precisión obtenida fue cercana al 85 %.1. INTRODUCCIÓN 2. MARCO DE REFERENCIA 3. METODOLOGÍA 4. ESTADO DEL ARTE 5. DESARROLLO 6. RESULTADOS 7. CONCLUSIONES 8. TRABAJO FUTURO BIBLIOGRAFÍA ANEXOSPregradoIngeniero de Sistema

Dark, Beyond Deep: A Paradigm Shift to Cognitive AI with Humanlike Common Sense

Recent progress in deep learning is essentially based on a "big data for small tasks" paradigm, under which massive amounts of data are used to train a classifier for a single narrow task. In this paper, we call for a shift that flips this paradigm upside down. Specifically, we propose a "small data for big tasks" paradigm, wherein a single artificial intelligence (AI) system is challenged to develop "common sense", enabling it to solve a wide range of tasks with little training data. We illustrate the potential power of this new paradigm by reviewing models of common sense that synthesize recent breakthroughs in both machine and human vision. We identify functionality, physics, intent, causality, and utility (FPICU) as the five core domains of cognitive AI with humanlike common sense. When taken as a unified concept, FPICU is concerned with the questions of "why" and "how", beyond the dominant "what" and "where" framework for understanding vision. They are invisible in terms of pixels but nevertheless drive the creation, maintenance, and development of visual scenes. We therefore coin them the "dark matter" of vision. Just as our universe cannot be understood by merely studying observable matter, we argue that vision cannot be understood without studying FPICU. We demonstrate the power of this perspective to develop cognitive AI systems with humanlike common sense by showing how to observe and apply FPICU with little training data to solve a wide range of challenging tasks, including tool use, planning, utility inference, and social learning. In summary, we argue that the next generation of AI must embrace "dark" humanlike common sense for solving novel tasks.Comment: For high quality figures, please refer to http://wellyzhang.github.io/attach/dark.pd