Validating TrueAllele® DNA mixture interpretation

Abstract: DNA mixtures with two or more contributors are a prevalent form of biological evidence. Mixture interpretation is complicated by the possibility of different genotype combinations that can explain the short tandem repeat (STR) data. Current human review simplifies this interpretation by applying thresholds to qualitatively treat STR data peaks as all‐or‐none events and assigning allele pairs equal likelihood. Computer review, however, can work instead with all the quantitative data to preserve more identification information. The present study examined the extent to which quantitative computer interpretation could elicit more identification information than human review from the same adjudicated two‐person mixture data. The base 10 logarithm of a DNA match statistic is a standard information measure that permits such a comparison. On eight mixtures having two unknown contributors, we found that quantitative computer interpretation gave an average information increase of 6.24 log units (min = 2.32, max = 10.49) over qualitative human review. On eight other mixtures with a known victim reference and one unknown contributor, quantitative interpretation averaged a 4.67 log factor increase (min = 1.00, max = 11.31) over qualitative review. This study provides a general treatment of DNA interpretation methods (including mixtures) that encompasses both quantitative and qualitative review. Validation methods are introduced that can assess the efficacy and reproducibility of any DNA interpretation method. An in‐depth case example highlights 10 reasons (at 10 different loci) why quantitative probability modeling preserves more identification information than qualitative threshold methods. The results validate TrueAllele^® DNA mixture interpretation and establish a significant information improvement over human review.     

Temporal variation of oxygen isotope ratios (δ18O) in drinking water: implications for specifying location of origin with human scalp hair

Previous work suggests that δ(18)O values of human hair can be used to constrain the region-of-origin of unknown individuals, but robust assessments of uncertainties in this method are lacking. Here we assess one source of uncertainty - temporal variation in the δ(18)O value of drinking water - using a monthly tap water survey of δ(18)O to develop geospatial models (i.e., maps) of the intra-annual variation (seasonality) in tap water δ(18)O for the contiguous USA. Temporal variation in tap water δ(18)O was correlated with water-supply type, and was related to geographic patterns of precipitation δ(18)O seasonality and water residence time. The maps were applied in a Bayesian framework to identify the geographic origin of an unidentified woman found in Utah, based on measured δ(18)O of scalp hair. The results are robust in specifying parts of the western USA as the most likely region-of-origin. Incorporation of tap water δ(18)O seasonality in the analysis reduces the precision of geographic assignments, but other sources of uncertainty (e.g., spatial interpolation uncertainty) have an equal or larger effect.     

Measuring the impact of law enforcement on organized crime

This article explores the possibility of measuring the impact of law enforcement on organized crime in a reliable and accountable manner, both in general terms and with a practical focus on the Canadian context. In considering measures to combat organized crime, a focus on process measurement has obscured the more substantial question of progress as regards the dependent variable itself: the bottom line of reducing the impact of organized criminal behaviour. While outcome measures are more challenging to identify than process measures, this fact alone does not minimize the need to demonstrate the connection between organized crime enforcement and its presumed outcomes to a greater degree of certainty. To date, this has not been realized to any significant degree, as revealed by a review of existing international approaches to measuring the impact of enforcement activity. The article argues that a multidisciplinary focus on community level indicators of crime, if initially less accessible than process measures of impact on organized crime groups, offers promise as a measurement of absolute and relative impact of state investment in enforcement.

Constituent Communication Through Telephone Town Halls: A Field Experiment Involving Members of Congress

Telephone town halls are an increasingly prevalent method for members of Congress (MCs) to communicate with constituents, even while garnering popular criticism for failing to facilitate engagement and accountability. Yet scholars have paid little attention to the events and their effects, and even less to how they might be improved. To remedy this problem, we report on a field experiment in which four MCs joined their constituents in telephone town halls. Overall, participation in an event improved constituents’ evaluations of the format in general, and of the MC in particular. Furthermore, we studied how these events might be improved by evaluating a reform—a single‐topic focus with predistributed briefing materials—designed to enhance deliberative interaction. This reform enhanced effects on opinions of the format without significantly altering effects on attitudes toward the MC. Our results suggest that telephone town halls hold promise for constituents, officeholders, and democratic practice.