Risk illusion and organized irresponsibility in contemporary finance: rethinking class and risk society

Abstract

This paper analyzes the lead-up to and aftermath of the 2008 financial crisis to show how processes associated with risk society – the social production and distribution of systemic financial risk in a context of organized irresponsibility – are contributing to the intensification of contemporary class-based inequalities. Utilizing a framework based in Bourdieusian class resources, the analysis moves beyond Beck's rejection of the relevance of class relations to systemic risk, and his critics’ denial that risk transforms existing logics of distribution, to identify key shifts in the relation between contemporary financial risk, power and inequality. The conclusions of this study, showing how systemic financial risk in contexts of organized irresponsibility contributes to differential ‘risk-classes’, suggest that risk is a key source of contemporary inequality and that reconstructing the theory of risk society can illuminate these changes.     

LoComatioN: a software tool for the analysis of low copy number DNA profiles

Previously, the interpretation of low copy number (LCN) STR profiles has been carried out using the biological or 'consensus' method-essentially, alleles are not reported, unless duplicated in separate PCR analyses [P. Gill, J. Whitaker, C. Flaxman, N. Brown, J. Buckleton, An investigation of the rigor of interpretation rules for STRs derived from less than 100 pg of DNA, Forens. Sci. Int. 112 (2000) 17-40]. The method is now widely used throughout Europe. Although a probabilistic theory was simultaneously introduced, its time-consuming complexity meant that it could not be easily applied in practice. The 'consensus' method is not as efficient as the probabilistic approach, as the former wastes information in DNA profiles. However, the theory was subsequently extended to allow for DNA mixtures and population substructure in a programmed solution by Curran et al. [J.M. Curran, P. Gill, M.R. Bill, Interpretation of repeat measurement DNA evidence allowing for multiple contributors and population substructure, Forens. Sci. Int. 148 (2005) 47-53]. In this paper, we describe an expert interpretation system (LoComatioN) which removes this computational burden, and enables application of the full probabilistic method. This is the first expert system that can be used to rapidly evaluate numerous alternative explanations in a likelihood ratio approach, greatly facilitating court evaluation of the evidence. This would not be possible with manual calculation. Finally, the Gill et al. and Curran et al. papers both rely on the ability of the user to specify two quantities: the probability of allelic drop-out, and the probability of allelic contamination ("drop-in"). In this paper, we offer some guidelines on how these quantities may be specified.     

A MCMC method for resolving two person mixtures

In this paper a Monte Carlo Markov Chain (MCMC) method for resolving DNA mixtures containing at most four peaks per locus into a major and a minor contributor is presented. Unlike previous methods, this method can provide posterior probability assessments of the most probable genotype and a likely range for the mixing proportion. The proposed method is applied to two DNA mixtures where the true genotypes of the contributors are known. The method provides posterior probabilities of the genotypes of the contributes which concord strongly with the known facts.     

The consequences of potentially differing distributions of the refractive indices of glass fragments from control and recovered sources

In forensic cases involving glass evidence, the variance of the recovered glass refractive index (RI) has been observed to be larger than the variance of the control glass RI. This has consequences for subsequent interpretation. To investigate this phenomenon, a study was made of the probable distributions of refractive indices of the recovered glass given a range of casework type scenarios involving breakage and backscatter. An investigation of the consequences of any distribution differences with regard to casework was also made. It was discovered that the inclusion of surface fragments from the float surface of the glass can have a profound effect on the comparison of recovered and control glass samples. The effect was largest when a breaker was striking the float surface of a window. In particular, it was found that the inclusion of a few surface fragments even post grouping is sufficient by itself to explain the observed differences in variance of RI between control and recovered groups. Surface fragments, if present, are very likely to be treated as outliers and to be deemed as non-matching. The findings of this paper challenge routine glass examination procedure and suggest that knowledge of which surface is facing the striker is valuable information in interpretation.     

Quantifying Uncertainty in Estimations of the Total Weight of Drugs in Groups of Complex Matrices

In case practice at forensic drug departments, multiple items from one seizure are sometimes sent in with the question: what is the total amount of drugs in the seizure? This may be complicated especially if impregnated material is involved such as clothes or rubber. Measurement uncertainty is typically stable on drug percentages, not weights, and subsampling may take place. It is recognized more and more that determination and reporting of uncertainty on estimators are an essential part of obtaining scientifically sound results in the forensic field. Methodology is described to quantify uncertainty on estimations of the total drug weight in groups of complex matrices, given simple statistical models, along a subdivision of five types of cases. Given each of these types, case examples are given where uncertainty is quantified in estimations of drug weights, by means of confidence intervals. The described models are statistically sound and relatively easy to implement.     

Physical attractiveness, issue agreement, and assimilation effects in candidate appraisal

This study examines the cognitive and affective factors of candidate appraisal by manipulating candidate attractiveness and levels of issue agreement with voters. Drawing upon research in evolutionary psychology and cognitive neuroscience, this analysis proposes that automatic processing of physical appearance predisposes affective disposition toward more attractive candidates, thereby influencing cognitive processing of issue information. An experimental design presented attractive and unattractive candidates who were either liberal or conservative in a mock primary election. The data show strong partial effects for appearance on vote intention, an interaction between appearance and issue agreement, and a tendency for voters to assimilate the dissimilar views of attractive candidates. We argue that physical appearance is important in primary elections when the differences in issue positions and ideology between candidates is small.     

The evaluation of human hand odor volatiles on various textiles: a comparison between contact and noncontact sampling methods

The focus of this study is to compare contact and noncontact human scent collection procedures across an array of textiles (cotton, rayon, polyester, and wool) to determine an optimized collection method for human scent evidence. Six subjects were sampled in triplicate for each textile and collection mode, and the samples were then analyzed through headspace solid-phase micro-extraction in combination with gas chromatography/mass spectrometry (SPME-GC/MS). Contact sampling with cotton material has been shown to be the collection method that yielded the greatest number of volatile compounds and the highest scent mass amounts. Through Spearman rank correlations, it was shown that an individual's scent profile is more reproducible within samples collected on the same textile type than between different materials. Furthermore, contact sampling with cotton fabric demonstrated the greatest reproducibility producing the lowest amount of type I and type II errors with 90.85% of the samples distinguished at the 0.9 match/no match threshold.     

Teacher victimization,turnover, and contextual factors promoting resilience

Teacher victimization is a relatively understudied phenomenon that may contribute to teacher turnover. The purpose of this study is to explore the relationship between teacher reports of victimization and teachers leaving their school and the profession. Using nationally representative data (n = 104,840) from the Schools and Staffing Survey, we examine the extent to which being threatened or attacked by students predicts higher rates of teacher turnover and whether this relationship differs due to factors that may promote teacher resilience. We utilize conditional multinomial logistic regression, implicitly controlling for school-by-year fixed effects. Findings suggest that perceived victimization predicts an increased probability of leaving the school and profession. School-level promoters of resilience are found to lessen this relationship. We discuss ways schools can mitigate the impact of victimization. This work contributes to a nascent body of literature on teacher victimization and informs a policy lever by which turnover may be reduced.