The Impact of Training and Language Competence on Judicial Application of EU Law in Hungary

The aim of this research is to identify the role that training in EU law and in a foreign language play in the use of EU law by Hungarian judges in domestic proceedings. Judges in the new Member States face the problems of no or inadequate official EU translations of relevant EU law or case‐law. The need to compare the meaning of other language versions therefore comes into play in order that the judges comply with the requirements of Union loyalty in the Treaty on European Union: Hungarian judges are shown to exhibit certain creative responses to these challenges. The approach to the research is based on an examination of the institutional framework for judicial training, a selection of pertinent case‐law of the Hungarian courts as well as interviews with a number of judges involved in the application of EU law in their courts.     

Potential Benefits from a Deep EU–India Free Trade Agreement

Both parties to an eventual EU India FTA have agreed that it should not merely address tariff barriers but should also go further into what is known as deep integration, originally developed in the 1990s by R.Z. Lawrence. This relates to the removal of all obstacles to cross border business whether actual trade barriers or domestic regulations. We distinguish deep institutional integration from the deep integration of markets. We ask the question how one may support the other. There are potential market failures that can be addressed by trans-national rules on standards and technical regulations and services, but we conclude that the biggest impact of a deep RTA would be on the domestic economy of India if it provides an opportunity for reform. It should be noted that the paper draws on a study undertaken by the authors for DG Trade, but it represents only the views of the authors.

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The dynamic political economy of support for Barack Obama during the 2008 presidential election campaign

In recent years, students of voting behavior have become increasingly interested in valence politics models of electoral choice. These models share the core assumption that key issues in electoral politicds typically are ones upon which there is a widespread public consensus on the goals of public policy. The present paper uses latent curve modeling procedures and data from a six-wave national panel survey of the American electorate to investigate the dynamic effects of voters’ concerns with the worsening economy—a valence issue par excellence—in the skein of causal forces at work in the 2008 presidential election campaign. As the campaign developed, the economy became the dominant issue. Although the massively negative public reaction to increasingly perilous economic conditions was not the only factor at work in 2008, dynamic multivariate analyses show that mounting worries about the economy played an important role in fueling Barack Obama’s successful run for the presidency.     

The effect of misperception on strategic behavior in legislative settings: Social psychology meets rational choice

This paper is about the conditions under which simple social psychological processes can affect collective decisions. In rational choice theory, social psychological effects are said to cancel out, be randomized, or be corrected by communication. Yet as Janis and Mann (1977) argued, there are generally recurring conditions in which such factors influence individual decisions. The question is, Under what conditions can we expect these factors to affect collective decisions? This paper suggests a general approach to identifying the effects of strategic misperception, illustrates it with an example of a social psychological process that affects player perceptions, and describes the preference distributions in which this simple process would change majority voting outcomes. The general conclusion is that strategic misperception may affect majority decisions under so many distributions of preferences that decisions cannot be predicted from knowledge of actors' preferences alone.     

Race,Place, and Police-Caused Homicide in U.S. Municipalities

We test structural hypotheses regarding police-caused homicides of minorities. Past research has tested minority threat and community violence hypotheses. The former maintains that relatively large minority populations are subjectively perceived as threats and experience a higher incidence of police-caused homicide than whites do, the latter that higher rates of violent crime among minorities create objective threats that explain these disparities. That research has largely ignored some important issues, including: alternative specifications of the minority threat hypothesis; the place hypothesis, which maintains highly segregated minority populations are perceived as especially threatening by police; and police-caused homicide in the Hispanic population. Using data for large U.S. cities, we conducted total-incidence and group-specific analyses to address these issues. A curvilinear minority threat hypothesis was supported by the Hispanic group-specific findings, whereas the place hypothesis found strong support in both total and group-specific analyses. These results provide new insights into patterns of police-caused homicide.     

公共服务中的政府、企业与社会三方合作

政府、企业与社会组织三方合作提供公共服务的模式在过去几十年里发展得非常迅速 ,在各国实践中摸索出的许多保证合作效能和服务质量的基本形式和组织框架很值得我们借鉴。     

Validating TrueAllele® DNA mixture interpretation

Abstract: DNA mixtures with two or more contributors are a prevalent form of biological evidence. Mixture interpretation is complicated by the possibility of different genotype combinations that can explain the short tandem repeat (STR) data. Current human review simplifies this interpretation by applying thresholds to qualitatively treat STR data peaks as all‐or‐none events and assigning allele pairs equal likelihood. Computer review, however, can work instead with all the quantitative data to preserve more identification information. The present study examined the extent to which quantitative computer interpretation could elicit more identification information than human review from the same adjudicated two‐person mixture data. The base 10 logarithm of a DNA match statistic is a standard information measure that permits such a comparison. On eight mixtures having two unknown contributors, we found that quantitative computer interpretation gave an average information increase of 6.24 log units (min = 2.32, max = 10.49) over qualitative human review. On eight other mixtures with a known victim reference and one unknown contributor, quantitative interpretation averaged a 4.67 log factor increase (min = 1.00, max = 11.31) over qualitative review. This study provides a general treatment of DNA interpretation methods (including mixtures) that encompasses both quantitative and qualitative review. Validation methods are introduced that can assess the efficacy and reproducibility of any DNA interpretation method. An in‐depth case example highlights 10 reasons (at 10 different loci) why quantitative probability modeling preserves more identification information than qualitative threshold methods. The results validate TrueAllele^® DNA mixture interpretation and establish a significant information improvement over human review.