A Proposed Scheme for Classifying Pediatric Rib Head Fractures Using Case Examples

Pediatric rib head fractures are typically described as “posterior” or “costovertebral,” terms lacking specificity. To resolve this issue, a scheme was developed to describe the location of rib head fractures observed in a pediatric forensic population. The scheme uses three anatomical landmarks, terminus (tip), tubercle, and costovertebral articular surface to divide the rib head into two subregions, costovertebral and costotransverse. Examples of five cases of infants with rib head fractures are presented using this scheme. Forty‐eight rib head fractures were observed in these infants with the following frequencies: 56% (three infants) at the terminus; 21% (three infants) in the costovertebral subregion; 21% (one infant) at the costovertebral articular facet; and 2% (one infant) in the costotransverse subregion. Due to the small number of cases assessed, statistical analyses could not be performed; however, the data demonstrate the variation in distribution of pediatric rib head fractures.     

Microscopic Saw Mark Analysis: An Empirical Approach

Microscopic saw mark analysis is a well published and generally accepted qualitative analytical method. However, little research has focused on identifying and mitigating potential sources of error associated with the method. The presented study proposes the use of classification trees and random forest classifiers as an optimal, statistically sound approach to mitigate the potential for error of variability and outcome error in microscopic saw mark analysis. The statistical model was applied to 58 experimental saw marks created with four types of saws. The saw marks were made in fresh human femurs obtained through anatomical gift and were analyzed using a Keyence digital microscope. The statistical approach weighed the variables based on discriminatory value and produced decision trees with an associated outcome error rate of 8.62–17.82%.     

The Politics of Obstruction: Republican Holds in the U.S. Senate

A defining feature of the modern US Senate is obstruction. Almost all pieces of legislation considered in the Senate are affected either directly or indirectly by obstruction. Obstruction takes many forms in the modern Senate, but one of the most prevalent, yet least studied, is the hold. Using a newly created dataset on Republican Senate holds, we cast light on this important practice. Our results suggest that a variety of factors including timing, party status, and a senator's voting record are related to both the prevalence of holds and the success of legislation subject to holds in the Senate.     

Rethinking the Roots of Terrorism: Beyond Orthodox Terrorism Theory—A Critical Research Agenda∗

The orthodox understanding of terrorism does not seem to provide adequate means for explaining the root causes of terrorism. This study is an attempt to critically rethink the roots of terrorism by relocating the study of terrorism into a conceptual space in which it can gain access to the tools provided by conflict studies. As a result this work addresses a gap in the field of terrorism studies and provides an explanation and clarification of the existence of orthodox terrorism discourse and the creation of an alternative theoretical framework for rethinking the roots of terrorism.     

The detection of simulated amnesia

Claims of amnesia are frequently raised in criminal and civil cases. There is a consensus in the legal community that amnesia is easily faked and practically impossible to disprove, and that many who claim to be amnesic are malingering. The present studies compared, on a variety of memory tasks, subjects instructed to simulate amnesia with subjects who had memory impairments due to brain damage. The simulators displayed patterns of performance different from those of memory-impaired subjects. These results suggest that lay-people have inaccurate beliefs about the cognitive features of amnesia, and do not distinguish among etiologically distinct amnestic disorders. Tasks that exploit lay-people's inaccurate beliefs about amnesia appear promising for the detection of malingering.     

Human capital,committee power and legislative outcomes

This paper presents a model in which legislators use informational asymmetries to engage in rent-seeking behavior. Previous work in the informational and distributive traditions could not explain deviations from the median preference without reference to “committee power”. Integration of these forces demonstrated that legislative outcomes need not correspond to the median preference regardless of the extent to which committee power is present in a legislature. While deviations from the median preference are consistent with committee power, recent empirical evidence suggests that observed deviations in Congress are in fact caused by human capital differentials rather than committee power.     

Qualitative comparative analysis vis-à-vis regression

Discussions of Charles C. Ragin’s Qualitative Comparative Analysis (QCA) have not adequately considered the assumptions about causation on which this method depends. Yet in evaluating any method, it is important to ask the question: How many untestable, or hard-to-test, assumptions must be met for us to believe the findings it produces? Advocates of QCA claim that one of its major strengths is that it requires fewer restrictive assumptions than techniques such as regression analysis. Hence, close assessment of the assumptions that are entailed is particularly salient to evaluating QCA. This article addresses these issues by considering three of the most important kinds of assumptions discussed in the context of regression analysis: assumptions about the correct form of the relationship, missing variables, and inferring causation from association. For each assumption, the role of corresponding assumptions in QCA will be explored and illustrated through an analysis of leftparty electoral fortunes in Latin America. Regarding the correct form of causal relationships, QCA in effect builds highly demanding assumptions into measurement procedures. Concerning missing variables, whereas earlier versions of QCA require a strong assumption of no causally relevant missing variables, more recent procedures allow some kinds of missing variables, but build in mutually contradictory statistical assumptions about those variables. Resolving these contradictions essentially converts QCA into an application of regression analysis. Regarding the process of inferring causation from association, QCA makes causal inference on the basis of patterns of association purely by assumption. That is, association is assumed to have a one-to-one relationship with causation. For all three groups of assumptions, QCA is found to require assumptions that, are at least as restrictive as those employed in regression analysis.