Beyond Attribution: Responsibility of Armed Non-State Actors for Reparations in Northern Ireland, Colombia and Uganda

This chapter explores the responsibility of armed non-state actors for reparations to victims. Traditionally international law has focused on the responsibility of the state, and more recently the responsibility of convicted individuals before the International Criminal Court, to provide reparations for international crimes. Yet despite the prevalence of internal armed conflict over the past few decades, there responsibility of armed groups for reparations has been neglected in international law. Although there is a tentative emerging basis for armed groups to provide reparations under international law, such developments have not yet crystallized into hard law. However, when considering the more substantive practice of states in Northern Ireland, Colombia and Uganda, a greater effort can be discerned in ensuring that such organizations are responsible for reparations. This paper finds that not only can armed non-state actors be held collectively responsible for reparations, but due to the growing number of internal armed conflict they can play an important role in ensuring the effectiveness of reparations in remedying victims’ harm. Yet, finding armed groups responsible for reparations is no panacea for accountability, due to the nature of armed conflicts, responsibility may not be distinct, but overlapping and joint, and such groups may face difficulties in meeting their obligations, thus requiring a holistic approach and subsidiary role for the state.

Age- and Sex-Specific Causal Effects of Adiposity on Cardiovascular Risk Factors

Observational studies have reported different effects of adiposity on cardiovascular risk factors across age and sex. Since cardiovascular risk factors are enriched in obese individuals, it has not been easy to dissect the effects of adiposity from those of other risk factors. We used a Mendelian randomization approach, applying a set of 32 genetic markers to estimate the causal effect of adiposity on blood pressure, glycemic indices, circulating lipid levels, and markers of inflammation and liver disease in up to 67,553 individuals. All analyses were stratified by age (cutoff 55 years of age) and sex. The genetic score was associated with BMI in both nonstratified analysis (P = 2.8 × 10(-107)) and stratified analyses (all P < 3.3 × 10(-30)). We found evidence of a causal effect of adiposity on blood pressure, fasting levels of insulin, C-reactive protein, interleukin-6, HDL cholesterol, and triglycerides in a nonstratified analysis and in the <55-year stratum. Further, we found evidence of a smaller causal effect on total cholesterol (P for difference = 0.015) in the ≥55-year stratum than in the <55-year stratum, a finding that could be explained by biology, survival bias, or differential medication. In conclusion, this study extends previous knowledge of the effects of adiposity by providing sex- and age-specific causal estimates on cardiovascular risk factors.

Children's use of interventions to learn causal structure

Children aged between 5 and 8 years freely intervened on a three-variable causal system, with their task being to discover whether it was a common-cause structure or one of two causal chains. From 6-7 years, children were able to use information from their interventions to correctly disambiguate the structure of a causal chain. We used a Bayesian model to examine children’s interventions on the system; this showed that with development children became more efficient in producing the interventions needed to disambiguate the causal structure and that the quality of interventions, as measured by their informativeness, improved developmentally. The latter measure was a significant predictor of children’s correct inferences about the causal structure. A second experiment showed that levels of performance were not reduced in a task in which children did not select and carry out interventions themselves, indicating no advantage for self-directed learning. However, children’s performance was not related to intervention quality in these circumstances, suggesting that children learn in a different way when they carry out interventions themselves.

Moral asymmetries in judgments of agency withstand ludicrous causal deviance

Americans have been shown to attribute greater intentionality to immoral than to amoral actions in cases of causal deviance, that is, cases where a goal is satisfied in a way that deviates from initially planned means (e.g., a gunman wants to hit a target and his hand slips, but the bullet ricochets off a rock into the target). However, past research has yet to assess whether this asymmetry persists in cases of extreme causal deviance. Here, we manipulated the level of mild to extreme causal deviance of an immoral versus amoral act. The asymmetry in attributions of intentionality was observed at all but the
most extreme level of causal deviance, and, as we hypothesized, was mediated by attributions of Blame/credit and judgments of action performance. These findings are discussed as they support a multiple-concepts interpretation of the asymmetry, wherein blame renders a naïve concept of intentional action (the outcome matches the intention) more salient than a composite concept (the outcome matches the intention and was brought about by planned means), and in terms of their implications for cross-cultural research on judgments of agency.

Effective network security monitoring: from attribution to target-centric monitoring

Network security monitoring remains a challenge. As global networks scale up, in terms of traffic, volume and speed, effective attribution of cyber attacks is increasingly difficult. The problem is compounded by a combination of other factors, including the architecture of the Internet, multi-stage attacks and increasing volumes of nonproductive traffic. This paper proposes to shift the focus of security monitoring from the source to the target. Simply put, resources devoted to detection and attribution should be redeployed to efficiently monitor for targeting and prevention of attacks. The effort of detection should aim to determine whether a node is under attack, and if so, effectively prevent the attack. This paper contributes by systematically reviewing the structural, operational and legal reasons underlying this argument, and presents empirical evidence to support a shift away from attribution to favour of a target-centric monitoring approach. A carefully deployed set of experiments are presented and a detailed analysis of the results is achieved.

Automated Equation Formulation for Causal Loop Diagrams

The annotation of Business Dynamics models with parameters and equations, to simulate the system under study and further evaluate its simulation output, typically involves a lot of manual work. In this paper we present an approach for automated equation formulation of a given Causal Loop Diagram (CLD) and a set of associated time series with the help of neural network evolution (NEvo). NEvo enables the automated retrieval of surrogate equations for each quantity in the given CLD, hence it produces a fully annotated CLD that can be used for later simulations to predict future KPI development. In the end of the paper, we provide a detailed evaluation of NEvo on a business use-case to demonstrate its single step prediction capabilities.