Tracing the Flow of Policy Ideas in Legislatures: A Text Reuse Approach

This article proposes a new approach to investigating the substance of lawmaking. Only a very small proportion of bills become law in the U.S. Congress. However, the bills that do become law often serve as vehicles for language originating in other bills. We investigate “text reuse” methods as a means for tracing the progress of policy ideas in legislation. We then show how a focus on policy ideas leads to new insights into the lawmaking process. Although our focus is on relating content found within bills, the same methods can be used to study policy substance across many research domains.     

Portable high‐resolution automated 3D imaging for footwear and tire impression capture

The forensic science community raised the need for improved evidence recognition, collection, and visualization analytical instrumentation for field and laboratory use. While the 3D optical techniques for imaging static objects have been extensively studied, there is still a major gap between current knowledge and collecting high‐quality footwear and tire impression evidence. Among optical means for 3D imaging, digital fringe projection (DFP) techniques reconstruct 3D shape from phase information, achieving camera‐pixel spatial resolution. This paper presents a high‐resolution 3D imaging technology using DFP techniques dedicated to footwear and tire impression capture. We developed fully automated software algorithms and a graphical user interface (GUI) that allow anyone without training to operate for high‐quality 3D data capture. We performed accuracy evaluations and comparisons comparing with the commercial high‐end 3D scanner and carried out qualitative tests for various impressions comparing with the current practices. Overall, our technology achieves similar levels of accuracy and resolution with a high‐end commercially available 3D scanner, while having the merits of being (1) more affordable; (2) much easier to operate; and (3) more robust. Compared with the current practice of casting, our technology demonstrates its superiority because it (1) is non‐destructive; (2) collects more evidence detail than casts, especially when an impression is fragile; (3) requires less time and money to collect each piece of evidence; and (4) results in a digital file that can easily be shared with other examiners.     

Estimating Individual Contributions to Complex DNA SNP Mixtures.,

High‐throughput sequencing (HTS) of large panels of single nucleotide polymorphisms (SNPs) provides an alternative or complimentary approach to short tandem repeats (STRs) panels for the analysis of complex DNA mixture forensic samples. For STRs, methods to estimate individual contribution concentrations compare capillary electrophoresis peak heights, peak areas, or HTS allele read counts within a mixture. This article introduces three approaches (mean, median, and slope methods) for estimating individual DNA contributions to forensic mixtures for HTS/massively parallel sequencing (MPS) SNP panels. For SNPs, the major:minor allele ratios or counts, unique to each contributor, were compared to estimate contributor proportion within the mixture using the mean, median, and slope intercept for these alleles. The estimates for these three methods were typically within 5% of planned experimental contributions for defined mixtures.     

Crafts and trades (english): Comment on T. Shanin

Eric Hobsbawm's outline of the concept of social banditry suggest certain conditions of existence for that mode of primitive rebellion. Primary among these conditions are the presence of a ‘traditional peasant environment and the absence of ‘industrial capitalism’. This paper presents a critique of Hobsbawm's specifications, and suggest two alternative conditions: the presence of class conflict which unites direct producers, and the absence of effective, institutionalised political organisation of producers’ interests. This reformulation is illustrated by reference to the Kelly Outbreak in late nineteenth century Australia.     

Predicting Children’s Depressive Symptoms from Community and Individual Risk Factors

Community, demographic, familial, and personal risk factors of childhood depressive symptoms were examined from an ecological theoretical approach using hierarchical linear modeling. Individual-level data were collected from an ethnically diverse (73% African-American) community sample of 197 children and their parents; community-level data were obtained from the U.S. Census regarding rates of community poverty and unemployment in participants’ neighborhoods. Results indicated that high rates of community poverty and unemployment, children’s depressive attributional style, and low levels of self-perceived competence predict children’s depressive symptoms, even after accounting for demographic and familial risk factors, such as parental education and negative parenting behaviors. The effect of negative parenting behaviors on depressive symptoms was partially mediated by personal variables like children’s self-perceived competence. Recommendations for future research, intervention and prevention programs are discussed.