Reassessing the alcohol-violence linkage: Results from a multiethnic city

This article examines the relationship between alcohol availability and nonlethal violence at the census-tract level in Miami, a multiethnic city with high levels of disadvantage and immigration. The effects of alcohol (total outlet rate) are considered from the perspectives of social disorganization and routine activities theories. Nonlethal violence is the average annual rates of robbery, aggravated assault, and total violence (combined aggravated assault and robbery). The analyses include corrections for spatial autocorrelation. The results show that alcohol availability has strong positive effects on rates of nonlethal violence and that the percentage of recent immigrants is also a significant positive predictor.     

The Impact of Pro-Government Militias on Human Rights Violations

New data show that between 1982 and 2007, in over 60 countries governments were linked to and cooperated with informal armed groups within their own borders. Given the prevalence of these linkages, we ask how such links between governments and informal armed groups influence the risk of repression. We draw on principal-agent arguments to explore how issues of monitoring and control help understanding of the impact of militias on human rights violations. We argue that such informal agents increase accountability problems for the governments, which is likely to worsen human rights conditions for two reasons. First, it is more difficult for governments to control and to train these militias, and they may have private interests in the use of violence. Second, informal armed groups allow governments to shift responsibility and use repression for strategic benefits while evading accountability. Using a global dataset from 1982 to 2007, we show that pro-government militias increase the risk of repression and that the presence of militias also affects the type of violations that we observe.     

Malware categorization using dynamic mnemonic frequency analysis with redundancy filtering

The battle between malware developers and security analysts continues, and the number of malware and malware variants keeps increasing every year. Automated malware generation tools and various detection evasion techniques are also developed every year. To catch up with the advance of malware development technologies, malware analysis techniques need to be advanced to help security analysts. In this paper, we propose a malware analysis method to categorize malware using dynamic mnemonic frequencies. We also proposed a redundancy filtering technique to alleviate drawbacks of dynamic analysis. Experimental results show that our proposed method can categorize malware and can reduce storage overheads of dynamic analysis.     

Chasing ghosts: An investigation of the ghosting phenomenon in footprints

Ghosting is a phenomenon that has been identified in dynamic (walking) footprints. There is sparse research on the occurrence of ghosting; however, due to the forensic value of footprints and their use in other scientific fields, the phenomenon of ghosting warrants further study. Ghosting can be used to determine if a footprint is static (standing) or dynamic, which can help forensic investigators create a sequence of events at a crime scene. Furthermore, this can help in footprint comparisons from this determination, as “like versus like” comparisons of dynamic or static footprints can be made. The purpose of this research was to determine the prevalence and locations of the ghosting phenomena in dynamic footprints.136 dynamic footprints from 68 volunteers were collected using an inkless collection system. Each footprint was visually inspected for ghosting as well as examined using software.Ghosting was present on at least one location in all footprints. The highest prevalence occurred at the tip of the great toe, followed by the second digit and the heel. To a lesser extent, ghosting appeared at the tips of the other three digits. Ghosting often occurred at two or more areas in a given footprint.     

Situational factors and police use of force across micro-time intervals: A video systematic social observation and panel regression analysis

The current study analyzes police use of force as a series of time-bound transactions between officers, civilians, and bystanders. The research begins with a systematic social observation of use-of-force events recorded on police body-worn cameras in Newark, New Jersey. Researchers measure the occurrence and time stamps for numerous participant physical and verbal behaviors. Data are converted into a longitudinal panel format measuring all observed behaviors in 5-second intervals. Panel logistic regression models estimate the effect of each behavior on use of force in immediate and subsequent temporal periods. Findings indicate certain variables influence use of force at a distinct point in time, whereas others exert influence on use of force across multiple time periods. The most influential variables relate to authority maintenance theoretical constructs. This finding supports prior perspectives arguing that police use of force largely results from officer attempts to maintain constant authority over civilians during face-to-face encounters. Nonetheless, a range of additional variables reflecting procedural justice, civilian resistance, and bystander presence significantly affect when police use force during civilian encounters. Results provide nuance to theoretical frameworks considering use of force as resulting from the interplay between officer and civilian actions and reactions.     

The British general election: Synthetic forecasts

Election forecasting work, in Britain and elsewhere, has been confined mainly to traditional approaches – statistical modeling or poll-watching. We import a new approach, which we call synthetic modeling. These models, developed out of forecasting efforts from the American 2012 presidential election, we are currently testing in a comparative European context. In this exercise, we apply the strategy to forecasting British general elections, in particular the upcoming 2015 contest. These synthetic forecasts come from hybrid models blending structural knowledge with contemporary public opinion. We generate ongoing nowcasts, from six months prior, to one month before, Election Day itself.     

Forecasting the 2015 British election through party popularity functions

To forecast the May 7, 2015 British General Election, we develop party popularity models based on Continuous Monitoring Survey (CMS) data from April 2004 to February 2015. Our models predict party vote shares three months prior to the election, using previous support levels, national economic evaluations, macro-partisanship and political measures. Our Seemingly Unrelated Regression (SUR) methodology allows us to predict support for the Tories, Labour, Liberal Democrats and “other” parties, separately, yet simultaneously, by constraining total support for all parties to 100%. Our model, estimated with data from February 2015, predicts that Labour will win the highest vote share in Great Britain, but that no party will win a majority of seats in parliament.     

Forecasting the 2015 British general election: The 1992 debacle all over again?

This article introduces and reviews a set of twelve academic forecasts of the 2015 British general election. Along with the vast majority of others including journalists and betting markets, they failed by a big margin to predict that the Conservatives would emerge with an overall majority of seats. Several suffered from the 1992 scale inaccuracies of the vote-intention opinion polls. Forecasts based on other data sources typically did a bit better, but also fell short. Nonetheless, this was not 1992 all over again. The dramatic collapse of the Liberal Democrats and rise of the SNP, UKIP and Greens were successfully anticipated. Also this collection includes numerous methodological advancements, with several new methods and developments to established approaches.     

Does the economy really matter for satisfaction with democracy? Longitudinal and cross-country evidence from the European Union

Research focusing on the relationship between the economy and satisfaction with democracy often presents mixed results. This article argues that this uncertainty is mainly due to model specification, number of surveys and measurement. After discussing why the role of the economy should not be overlooked, by using an empirical strategy that applies Bayesian cross-classified mixed models to 572 national surveys in 28 European countries from 1973 to 2013 drawn from the Eurobarometer, it is shown that objective macro-economic indicators and a subjective indicator seem to substantially affect citizens’ satisfaction with democracy in Europe. The findings are robust when controlling for various institutional and political variables and using alternative model specifications.     

Public confidence in the judiciary: the interaction between political awareness and level of democracy

Apart from the studies that focus on public attitudes toward higher courts in advanced democracies, we know little about the factors that can explain public confidence in the judiciary in a comparative setting. In this regard, the goal of this study is to explain whether, and to what extent, the country's level of democracy moderates the impact of political awareness on public confidence in the judiciary. This study uses hierarchical linear models to analyse the interaction between individual and country level factors by using the World Values Survey (2005–2009) data for 49 countries and various other data sources. Our empirical results show that in advanced democracies political awareness variables like education and political participation have a positive impact on public confidence in the judiciary, whereas in countries with weak levels of democracy higher political awareness leads to increased cynicism about the judiciary. These results suggest that a one-size-fits-all approach to explain confidence in the judiciary is not possible when we are dealing with a wide range of societies that vary in terms of many characteristics, both institutional and cultural.