Service-Seeking Behavior,Perceptions of Armed Actors,and Preferences Regarding Governance: Evidence from the Palestinian Territories

Armed non-state actors, such as Hezbollah and Hamas, are visibly engaged in providing social welfare in addition to participating in violence. A number of scholars have suggested that there is a relationship between service provision by terrorist organizations and support from service recipients, and have indicated that terrorist organizations use service provision strategically for this purpose. However, few studies have examined the experiences and opinions of service recipients themselves to understand if services do indeed influence populations' political loyalties and opinions regarding violent activities. Using data from more than 1,000 low to moderate income individuals in Palestine, this study seeks to understand if and how receiving services from a specific organization engenders loyalty to the organization, passive acceptance and/or favorable approval of the organizations' violent activities, and the likelihood of participation in the organization's violent activities. This paper explores if and how provision of aid and “governance” services by armed non-state actors is correlated with various aspects of individuals' experiences of conflict, such as their opinions about the use of violence and various strategies for attaining peace, their fellow community members' likelihood to join armed groups and engage in fighting, and their preferences regarding state structure and legal system.     

Spontaneous intracerebral hemorrhage related to methamphetamine abuse: autopsy findings and clinical correlation

A healthy 31-year-old male abstinent from drug abuse during his recent incarceration developed slurred speech, a severe headache, and left-sided hemiparesis prior to his eventual death 9.5 hours after inhalation of methamphetamine. On postmortem examination, inspection of the brain revealed bilateral subarachnoid hemorrhage, with a prominent intralobar hemorrhage centered within the right frontal cerebral hemisphere. No evidence of vasculitis, infarction, intraventricular hemorrhage, or ruptured aneurysm could be observed. While this is not the first report of a methamphetamine-related stroke, this report describes the autopsy findings of an intracerebral hemorrhage secondary to methamphetamine abuse on autopsy and compares the findings and antemortem history to previously reported methamphetamine cerebral vascular deaths.     

Assessing Stability and Change in Criminal Offending: A Comparison of Random Effects, Semiparametric, and Fixed Effects Modeling Strategies

An important theoretical problem for criminologists is an explanation forthe robust positive correlation between prior and future criminaloffending. Nagin and Paternoster (1991) have suggested that the correlationcould be due to time-stable population differences in the underlyingproneness to commit crimes (population heterogeneity) and/or thecriminogenic effect that crime has on social bonds, conventionalattachments, and the like (state dependence). Because of data andmeasurement limitations, the disentangling of population heterogeneityand state dependence requires that researchers control for unmeasuredpersistent heterogeneity. Frequently, random effects probit models havebeen employed, which, while user-friendly, make a strong parametricassumption that the unobserved heterogeneity in the population follows anormal distribution. Although semiparametric alternatives to the randomeffects probit model have recently appeared in the literature to avoid thisproblem, in this paper we return to reconsider the fully parametric model. Viasimulation evidence, we first show that the random effects probit modelproduces biased estimates as the departure of heterogeneity from normalitybecomes more substantial. Using the 1958 Philadelphia cohort data, we thencompare the results from a random effects probit model with a semiparametricprobit model and a fixed effects logit model that makes no assumptions aboutthe distribution of unobserved heterogeneity. We found that with this dataset all three models converged on the same substantive result—evenafter controlling for unobserved persistent heterogeneity, with models thattreat the unobserved heterogeneity very differently, prior conduct had apronounced effect on subsequent offending. These results are inconsistentwith a model that attributes all of the positive correlation between priorand future offending to differences in criminal propensity. Sinceresearchers will often be completely blind with respect to the tenabilityof the normality assumption, we conclude that different estimationstrategies should be brought to bear on the data.     

Sentencing Using Statistical Treatment Rules: What We Don’t Know Can Hurt Us

The existing literature seriously misinterprets the available evidence on the predictability of high rate criminal offending and thus the potential value of statistical treatment rules that impose stiffer punishments on offenders with higher predicted risk of recidivism. The misinterpretation results from the failure to take account of the fact that the data used in existing risk assessment exercises come from environments characterized by informal (and sometimes formal) attempts by judges and other actors to base penal treatments on expected recidivism. Findings of little or no predictive power for baseline covariates may simply indicate the efficient use of the available information. We lay out the problem in detail, provide examples from several literatures and then consider general solutions to the problem.

Identifying Classes of Explanations for Crime Drop: Period and Cohort Effects for New York State

Objective

This paper advances current understanding of the contemporary crime drop by focusing on the changes in the age distribution of arrests from 1990 to 2010. Using the New York State Computerized Criminal History (CCH) file, which tracks every arrest in the state, we apply standard demographic methods to examine age-specific arrest rates over time. We test whether the 25 % drop in the felony arrest rate can be best explained by period or cohort effects with special attention to how the phenomenon varies across crime types and regions within the state.

Methods

Following the analytic approach of O’Brien and Stockard (J Quant Criminol 25(1):79–101, 2009), we fit the age–period–cohort (APC) model using the generalized inverse matrix, which creates an estimable model. We partition the model variation into each factor by subtracting the variation of the two-factor model from the variation of the three-factor model to provide a direct comparison of the two different classes of explanations for crime drop: period and cohort.

Results

Our analysis supports a cohort explanation over a period explanation. Controlling for the (substantial) variation due to age, the cohort effect accounts for twice as much of the remaining variation as the period effect. Specifically, the drop in arrest rates is concentrated in more recent birth cohorts across all ages. Although we found statistically significant age–period interaction effects for the younger age group (ages 16–20) in 1990 and 1995, the cohort effect was still a much stronger predictor of felony arrest rates than the period explanation, even with the age–period interaction.

Conclusions

The current study reports that the overall drop in felony arrest rates from 1990 to 2010 is mostly due to decreased arrests among those who were born after 1970 rather than a universal drop across different age groups. We discuss but do not test two potential explanations—the legalization of abortion and the ban on leaded gasoline—for the underlying factors associated with a different criminal propensity among birth cohorts.