Why Assessing Estimative Accuracy is Feasible and Desirable

The US Intelligence Community (IC) has been heavily criticized for making inaccurate estimates. Many scholars and officials believe that these criticisms reflect inappropriate generalizations from a handful of cases, thus producing undue cynicism about the IC's capabilities. Yet there is currently no way to evaluate this claim, because the IC does not systematically assess the accuracy of its estimates. Many scholars and practitioners justify this state of affairs by claiming that assessing estimative accuracy would be impossible, unwise, or both. This article shows how those arguments are generally unfounded. Assessing estimative accuracy is feasible and desirable. This would not require altering existing tradecraft and it would address several political and institutional problems that the IC faces today.     

After Enactment: The Lives and Deaths of Federal Programs

While many scholars have focused on the production of legislation, we explore life after enactment. Contrary to the prevailing view that federal programs are indissoluble, we show that programmatic restructurings and terminations are commonplace. In addition, we observe significant changes in programmatic appropriations. We suggest that a sitting congress is most likely to transform, kill, or cut programs inherited from an enacting congress when its partisan composition differs substantially. To test this claim, we examine the postenactment histories of every federal domestic program established between 1971 and 2003, using a new dataset that distinguishes program death from restructuring. Consistent with our predictions, we find that changes in the partisan composition of congresses have a strong influence on program durability and size. We thus dispel the notion that federal programs are everlasting while providing a plausible coalition-based account for their evolution.     

The effect of misperception on strategic behavior in legislative settings: Social psychology meets rational choice

This paper is about the conditions under which simple social psychological processes can affect collective decisions. In rational choice theory, social psychological effects are said to cancel out, be randomized, or be corrected by communication. Yet as Janis and Mann (1977) argued, there are generally recurring conditions in which such factors influence individual decisions. The question is, Under what conditions can we expect these factors to affect collective decisions? This paper suggests a general approach to identifying the effects of strategic misperception, illustrates it with an example of a social psychological process that affects player perceptions, and describes the preference distributions in which this simple process would change majority voting outcomes. The general conclusion is that strategic misperception may affect majority decisions under so many distributions of preferences that decisions cannot be predicted from knowledge of actors' preferences alone.     

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.     

Obliging children

Children may sometimes undergo healthcare procedures that are not intended to improve their health status. Such interventions might include the use of young children as bone marrow donors or their enrolment in non-therapeutic research. One of the justifications used to legitimise these interventions is the premise that children have obligations to others; to their family in the case of related bone marrow transplantation, and to wider society in the case of non-therapeutic research. However, this 'obligation model' (the notion that children possess positive obligations to advance the health status of others) fails as a justificatory paradigm because it is based upon a confusion, identified by Hart, between two notions; that of 'being under an obligation to do something' and that of 'being obliged to do something'. Instead the 'obligation model' is a device employed to put a justificatory gloss upon a consequentialist decision-making process; removing the legitimising gloss allows for a more transparent look at the conflict between parental rights and an individual child's right to bodily integrity.