Assessing preferences in cost-benefit analysis: Reflections on rural water supply evaluation in haiti

This article examines an area of cost-benefit methodology which has come under increasing philosophical scrutiny in recent years: the appropriate treatment of individuals' preferences. We illustrate some of the difficulties involved in assessing preferences in the context of a concrete example: the evaluation of a rural water supply project in southern Haiti. Four problems in the application of cost-benefit principles are discussed: (1) how to count the social value of private water taps connected to homes if they are preferred for prestige reasons, (2) how to assess husbands' preferences concerning the time savings by wives who previously carried water from more distant sources, (3) how to count preferences based on a respondent's desire to support general community welfare, and (4) how to evaluate a water project when people's preferences may change after the new water system is installed. We argue that policy analysis will be improved by presenting philosophical arguments as to why some preferences should be included in the evaluation and others ignored.     

Identifying Fatal Head Injuries on Postmortem Computed Tomography Using Convolutional Neural Network/Deep Learning: A Feasibility Study

Postmortem computed tomography (PMCT) is a relatively recent advancement in forensic pathology practice that has been increasingly used as an ancillary investigation and screening tool. One area of clinical CT imaging that has garnered a lot of research interest recently is the area of “artificial intelligence” (AI), such as in screening and computer-assisted diagnostics. This feasibility study investigated the application of convolutional neural network, a form of deep learning AI, to PMCT head imaging in differentiating fatal head injury from controls. PMCT images of a transverse section of the head at the level of the frontal sinus from 25 cases of fatal head injury were combined with 25 nonhead-injury controls and divided into training and testing datasets. A convolutional neural network was constructed using Keras and was trained against the training data before being assessed against the testing dataset. The results of this study demonstrated an accuracy of between 70% and 92.5%, with difficulties in recognizing subarachnoid hemorrhage and in distinguishing congested vessels and prominent falx from head injury. These results are promising for potential applications as a screening tool or in computer-assisted diagnostics in the future.     

THE INTERNAL AND EXTERNAL VALIDITY OF THE REGRESSION DISCONTINUITY DESIGN: A META‐ANALYSIS OF 15 WITHIN‐STUDY COMPARISONS

Theory predicts that regression discontinuity (RD) provides valid causal inference at the cutoff score that determines treatment assignment. One purpose of this paper is to test RD's internal validity across 15 studies. Each of them assesses the correspondence between causal estimates from an RD study and a randomized control trial (RCT) when the estimates are made at the same cutoff point where they should not differ asymptotically. However, statistical error, imperfect design implementation, and a plethora of different possible analysis options, mean that they might nonetheless differ. We test whether they do, assuming that the bias potential is greater with RDs than RCTs. A second purpose of this paper is to investigate the external validity of RD by exploring how the size of the bias estimates varies across the 15 studies, for they differ in their settings, interventions, analyses, and implementation details. Both Bayesian and frequentist meta‐analysis methods show that the RD bias is below 0.01 standard deviations on average, indicating RD's high internal validity. When the study‐specific estimates are shrunken to capitalize on the information the other studies provide, all the RD causal estimates fall within 0.07 standard deviations of their RCT counterparts, now indicating high external validity. With unshrunken estimates, the mean RD bias is still essentially zero, but the distribution of RD bias estimates is less tight, especially with smaller samples and when parametric RD analyses are used.     

Longitudinal Bi-directional Relationships Between Sleep and Youth Substance Use

Despite the known deficits in sleep that occur during adolescence and the high prevalence of substance use behaviors among this group, relatively little research has explored how sleep and substance use may be causally related. The purpose of this study was to explore the longitudinal bi-directional relationships between sleep duration, sleep patterns and youth substance use behaviors. Participants included 704 mostly white (86.4?%) youth, 51?% female, with a baseline mean age of 14.7?years. Self-reported substance use behaviors included past month alcohol, cigarette, and marijuana use. Sleep measures included sleep duration on weekends and weekdays, total sleep, weekend oversleep, and weekend sleep delay. Cross-lagged structural equation models, accounting for clustering at the school level, were run to determine the longitudinal association between sleep and substance use adjusting for socio-demographic characteristics, pubertal status, body mass index z-score, and depressive symptoms. Cigarette use and weekend sleep were bi-directionally related as were marijuana use and total sleep. No other bi-directional associations were identified. However, alcohol use predicted shorter weekend oversleep and marijuana use predicted increased weekend sleep and weekend oversleep. Sleep patterns and duration also predicted adolescents' cigarette, alcohol, and marijuana use. Sleep, both patterns and duration, and substance use among youth are intertwined. Future research is needed to explore these bi-directional relationships, as well as other important contextual factors that may moderate these associations.     

Immigration and integration policy and the Austrian radical right in office: the FPÖ/BZÖ, 2000–2006

This article focuses on the radical right's influence on immigration and migrant integration policy by scrutinising the 6-year period in national government of the Austrian Freedom Party and Alliance for Austria's Future. Specifically, it investigates the radical right's influence on migration control, migrant integration, citizenship and asylum policy. While previous studies have often credited the Austrian radical right with policy influence, it is argued that such work ignores both the problematic adjustment of the radical right to public office and the insights of immigration policy theory. By integrating these criticisms into the analysis, it is argued that although immigration policy was restrictive, the policies pursued did not deviate too greatly from past and subsequent government policy nor with the policies being implemented elsewhere in Europe. Furthermore, the radical right's influence on immigration policy was limited by the role of intra-coalition dynamics and the moderating effect of the policy process.     

The wonderful world of patent drafting

To anyone involved in patent litigation, it is clear that thetask of drafting is not for the faint-hearted. Those who draftpatents are acutely aware of the pitfalls which await theirclients following even a mere slip of the pen. This commentator,who is daily involved in the pre-filing review and prosecutionof patents and, alongside clients, assisting lawyers in manycountries with patent litigation,     

Caffeine toxicity: a case of child abuse by drug ingestion

The case of a 14-month-old child who died of caffeine toxicity is presented. The evidence for prolonged toxicity associated with inappropriate delay in the seeking of medical care and the presence of various recent and healing injuries are diagnostic of child abuse. Fatal caffeine toxicity and child abuse by drug/substance administration are uncommonly reported. Relevant medical literature is reviewed.