Choosing Ungoverned Space: The Removal of Pakistan’s Frontier Crimes Regulation

Why do administratively competent states sometimes leave substantial swathes of their territory ungoverned? We explore this question in the context of the Frontier Crimes Regulation (FCR) in Pakistan, a British Colonial law only abrogated in 2018, that left legal decisions up to local customary councils. This contrasts with areas where the British and Pakistani state built modern political and bureaucratic institutions. Using primary legal documents we create a dataset of when and where FCR applied between 1901 and 2012. Exploiting spatial variation in the Green Revolution’s impact in the 1960s, we show that governance was preferentially extended to places where the state stood to benefit the most in terms of land revenue. Our results show that technological changes which shift the returns to control influence where states choose to govern

Can Hearts and Minds Be Bought? The Economics of Counterinsurgency in Iraq

We develop and test an economic theory of insurgency motivated by the informal literature and by recent military doctrine. We model a three-way contest between violent rebels, a government seeking to minimize violence by mixing service provision and coercion, and civilians deciding whether to share information about insurgents. We test the model using panel data from Iraq on violence against Coalition and Iraqi forces, reconstruction spending, and community characteristics (sectarian status, socio-economic grievances, and natural resource endowments). Our results support the theory‘s predictions: improved service provision reduces insurgent violence, particularly for smaller projects and since the "surge" began in 2007.

Predicting Adverse Outcomes in End Stage Renal Disease: Machine Learning Applied to the United States Renal Data System

We examined machine learning methods to predict death within six months using data derived from the United States Renal Data System (USRDS). We specifically evaluated a generalized linear model, a support vector machine, a decision tree and a random forest evaluated within the context of K-10 fold validation using the CARET package available within the open source architecture R program. We compared these models with the feed forward neural network strategy that we previously reported on with this data set

Do Working Men Rebel? Insurgency and Unemployment in Iraq and the Philippines

Most aid spending by governments seeking to rebuild social and political order is based on an opportunity-cost theory of distracting potential recruits. The logic is that gainfully employed young men are less likely to participate in political violence, implying a positive correlation between unemployment and violence in locations with active insurgencies. We test that prediction in Afghanistan, Iraq and the Philippines, using survey data on unemployment and two newly-available measures of insurgency: (1) attacks against government and allied forces; and (2) violence that kills civilians. Contrary to the opportunity-cost theory, the data emphatically reject a positive correlation between unemployment and attacks against government and allied forces (p

The Effect of Civilian Casualties in Afghanistan and Iraq

A central question in intrastate conflicts is how insurgents are able to mobilize supporters to participate in violent and risky activities. A common explanation is that violence committed by counterinsurgent forces mobilizes certain segments of the population through a range of mechanisms. We study the effects of civilian casualties in Iraq and Afghanistan to quantify the effect of such casualties on subsequent insurgent violence. By comparing uniquely detailed micro-data along temporal, spatial, and gender dimensions we can distinguish short-run 'information' and 'capacity' effects from the longer run 'propaganda' and 'revenge' effects. In Afghanistan we find strong evidence that local exposure to civilian casualties caused by international forces leads to increased insurgent violence over the long-run, what we term the 'revenge' effect. Matching districts with similar past trends in violence shows that counterinsurgent-generated civilian casualties from a typical incident are responsible for 1 additional violent incident in an average sized district in the following 6 weeks and lead to increased violence over the next 6 months. There is no evidence that out-of-area events—errant air strikes for example—lead to increased violence, nor is there evidence of short run effects, thus ruling out the propaganda, information, and capacity mechanisms. Critically, we find no evidence of a similar reaction to civilian casualties in Iraq, suggesting the constraints on insurgent production of violence may be quite conflict-specific. Our results imply that minimizing harm to civilians may indeed help counterinsurgent forces in Afghanistan to reduce insurgent recruitment.

Navigating the Web of Misinformation: A Framework for Misinformation Domain Detection Using Browser Traffic

The proliferation of misinformation and propaganda is a global challenge, with profound effects during major crises such as the COVID-19 pandemic and the Russian invasion of Ukraine. Understanding the spread of misinformation and its social impacts requires identifying the news sources spreading false information. While machine learning (ML) techniques have been proposed to address this issue, ML models have failed to provide an efficient implementation scenario that yields useful results. In prior research, the precision of deployment in real traffic deteriorates significantly, experiencing a decrement up to ten times compared to the results derived from benchmark data sets. Our research addresses this gap by proposing a graph-based approach to capture navigational patterns and generate traffic-based features which are used to train a classification model. These navigational and traffic-based features result in classifiers that present outstanding performance when evaluated against real traffic. Moreover, we also propose graph-based filtering techniques to filter out models to be classified by our framework. These filtering techniques increase the signal-to-noise ratio of the models to be classified, greatly reducing false positives and the computational cost of deploying the model. Our proposed framework for the detection of misinformation domains achieves a precision of 0.78 when evaluated in real traffic. This outcome represents an improvement factor of over ten times over those achieved in previous studies

Aggregation Patterns in Stressed Bacteria

We study the formation of spot patterns seen in a variety of bacterial species when the bacteria are subjected to oxidative stress due to hazardous byproducts of respiration. Our approach consists of coupling the cell density field to a chemoattractant concentration as well as to nutrient and waste fields. The latter serves as a triggering field for emission of chemoattractant. Important elements in the proposed model include the propagation of a front of motile bacteria radially outward form an initial site, a Turing instability of the uniformly dense state and a reduction of motility for cells sufficiently far behind the front. The wide variety of patterns seen in the experiments is explained as being due the variation of the details of the initiation of the chemoattractant emission as well as the transition to a non-motile phase.Comment: 4 pages, REVTeX with 4 postscript figures (uuencoded) Figures 1a and 1b are available from the authors; paper submitted to PRL

The role of election competition in strengthening Pakistan’s fledgling local democracy

Using results and original survey data from the November 2015 local government elections in the Sargodha District of rural Punjab, Pakistan, insights are offered into the institutional and organisational responses that can help strengthen local democracy. These results form part of a larger research project being conducted by the Institute of Development and Economic Alternatives (IDEAS), which examines how voters make choices broadly. It explores the relative weight voters give to party performance vs. candidates’ political and bureaucratic connections. It highlights the need for reporting, debate and a rule-based separation of functions and finances to strengthen local democracy in Pakistan