Interest group networks in the European Union

Interest group networks are crucial for understanding European Union (EU) integration, policymaking and interest representation. Yet, comparative analysis of interest organisation networks across EU policy areas is limited. This study provides the first large-scale investigation of interest group information networks across all EU policy domains. We argue that interest groups prioritise access to trustworthy and high-quality information coming from partners with shared policy goals. Thus, interest organisations form network ties with other organisations if the latter are from the same country, represent the same type of interest, or are policy insiders. The effect of these three factors varies across policy domains depending on the extent to which the institutional setting assures equal and broad organisational access to decision-making. Our empirical analysis operationalises information ties as Twitter-follower relationships among 7,388 interest organisations. In the first step of the analysis, we use Exponential Random Graph Models to examine tie formation in the full network and across 40 policy domains. We find strong but variable effects of country and interest type homophily and policy insiderness on the creation of network ties. In the second step, we examine how the effect of these three variables on tie formation varies with policy domain characteristics. We find that shared interest type and policy insiderness are less relevant for tie formation in (re-)distributive and especially regulatory policy domains characterised by more supranational decision-making. Sharing an interest type and being a policy insider matters more for tie formation in foreign and interior policies where decision-making is more intergovernmental. The effect of country homophily is less clearly related to policy type and decision-making mode. Our findings emphasise the importance of institutional and policy context in shaping interest group networks in the EU.     

关于推定的基础事实的证明标准的思考

排除合理怀疑作为刑事诉讼的认证标准已得到理论界的普遍重视，但是在民事推定中也应该引用此标准。为了保证民事推定的判决的公正性，在民事推定的基础事实的认定中采用“排除合理怀疑”的认证标准是现实的、必须的。生效的民事裁判中不符合此标准而认定的事实也不能作为民事推定的基础事实。有关证据法民事推定规则的设计应当对此加以明确。     

由证明标准析附带民诉制度

附带民诉以刑诉为制度设计出发点,其首要目标在于完成查明、制控与惩罚犯罪的刑事政策目的,保护被害人私权只是其第二位的目标。由于民、刑诉在证明标准上的差异,理论上存在只顾及刑诉,而不保障其附带之民诉的正义实现这一情形,此时对附带之民诉的裁判更难实现诉讼正义。应在立法上摈弃客观真实,采纳民、刑诉二元化的证明标准,同时给予法官一定的自由裁量权,这样才能保障附带之民诉部分的正义。     

司法公正与效率视野下的民事诉讼证明标准探讨

本文考察了英美法系与大陆法系国家的诉讼证明标准,指出了民事诉讼的证明标准与刑事诉讼证明标准的差异后,以司法公正和司法效率为支点,对传统上的“客观真实”的证明标准提出质疑,主张建立以“法律真实”为诉讼价值目标,以“盖然性占优势”的证明标准为主,而以在一些特殊案件实行“高度盖然性”证明标准为辅的民事诉讼证明标准。最后,文章还关注法学界和司法审判的最新动态,探讨了“盖然性占优势”与“高度盖然性”证明标准在审判实践中的具体运用及其应该注意的问题。     

A MULTILEVEL TEST OF RACIAL THREAT THEORY

We develop a conceptual model articulating the mechanisms by which racial threat is theorized to affect social control, focusing specifically on the influence of the relative size of the black population on the likelihood that the police will arrest a black citizen suspected of a violent criminal offense. A multilevel analysis of 145, 255 violent crimes reported to police in 182 cities during 2000 shows only qualified support for racial threat theory. Controlling for the amount of race-specific crime reported to police, our findings reveal that black citizens actually have a lower probability of arrest in cities with a relatively large black population. This finding tends to cast doubt on the validity of the racial threat hypothesis. No evidence buttresses the claim that economic competition between whites and blacks affects arrest probabilities. However, results show that in cities where racial segregation is more pronounced blacks have a reduced risk sof being arrested relative to whites. Crimes involving black offenders and white victims are also more apt to result in an arrest in cities that are racially segregated. These findings support the view that racial segregation is an informal mechanism to circumscribe the threat of potentially volatile subordinate populations.     

Ancestry Assessment Using Random Forest Modeling, ,

A skeletal assessment of ancestry relies on morphoscopic traits and skeletal measurements. Using a sample of American Black (n = 38), American White (n = 39), and Southwest Hispanics (n = 72), the present study investigates whether these data provide similar biological information and combines both data types into a single classification using a random forest model (RFM). Our results indicate that both data types provide similar information concerning the relationships among population groups. Also, by combining both in an RFM, the correct allocation of ancestry for an unknown cranium increases. The distribution of cross‐validated grouped cases correctly classified using discriminant analyses and RFMs ranges between 75.4% (discriminant function analysis, morphoscopic data only) and 89.6% (RFM). Unlike the traditional, experience‐based approach using morphoscopic traits, the inclusion of both data types in a single analysis is a quantifiable approach accounting for more variation within and between groups, reducing misclassification rates, and capturing aspects of cranial shape, size, and morphology.     

Comparisons of familial DNA database searching strategies

The current familial searching strategies are generally based on either Identity-By-State (IBS) (i.e., number of shared alleles) or likelihood ratio (i.e., kinship index [KI]) assessments. In this study, the expected IBS match probabilities given relationships and the logic of the likelihood ratio method were addressed. Further, the false-positive and false-negative rates of the strategies were compared analytically or by simulations using Caucasian population data of the 13 CODIS Short Tandem Repeat (STR). IBS ≥ 15, IBS ≥ 16, KI ≥ 1000, or KI ≥ 10,000 were found to be good thresholds for balancing false-positive and false-negative rates. IBS ≥ 17 and/or KI ≥ 1,000,000 can exclude the majority of candidate profiles in the database, either related or not, and may be an initial screening option if a small candidate list is desired. Polices combining both IBS and KI can provide higher accuracy. Typing additional STRs can provide better searching performance, and lineage markers can be extremely useful for reducing false rates.     

Using automated comparisons to quantify handwriting individuality

The proposition that writing profiles are unique is considered a key premise underlying forensic handwriting comparisons. An empirical study cannot validate this proposition because of the impossibility of observing sample documents written by every individual. The goal of this paper is to illustrate what can be stated about the individuality of writing profiles using a database of handwriting samples and an automated comparison procedure. In this paper, we provide a strategy for bounding the probability of observing two writers with indistinguishable writing profiles (regardless of the comparison methodology used) with a random match probability that can be estimated statistically. We illustrate computation of this bound using a convenience sample of documents and an automated comparison procedure based on Pearson's chi-squared statistic applied to frequency distributions of letter shapes extracted from handwriting samples. We also show how this bound can be used when designing an empirical study of individuality.     

Bayesian networks and the value of the evidence for the forensic two-trace transfer problem*

Forensic scientists face increasingly complex inference problems for evaluating likelihood ratios (LRs) for an appropriate pair of propositions. Up to now, scientists and statisticians have derived LR formulae using an algebraic approach. However, this approach reaches its limits when addressing cases with an increasing number of variables and dependence relationships between these variables. In this study, we suggest using a graphical approach, based on the construction of Bayesian networks (BNs). We first construct a BN that captures the problem, and then deduce the expression for calculating the LR from this model to compare it with existing LR formulae. We illustrate this idea by applying it to the evaluation of an activity level LR in the context of the two-trace transfer problem. Our approach allows us to relax assumptions made in previous LR developments, produce a new LR formula for the two-trace transfer problem and generalize this scenario to n traces.