Social pressure and the making of wartime civilian protection rules

The protection of civilians from the dangers of warfare constitutes an imperative in contemporary global politics. Drawing on original multiarchival research, this article explains the codification of the core civilian protection rules within international humanitarian law in the 1970s. It argues that these crucial international rules resulted from the operation of two central mechanisms: Third World and Socialist-led social pressure and a strategic, face-saving reaction to it, leadership capture, in the politicized context of Cold War and decolonization-era international social competition. I demonstrate the conditional effect of social pressure by a coalition of materially weaker Third World and Socialist states upon powerful reluctant states: the United States, the United Kingdom, and more surprisingly, the Soviet Union. Third World and Socialist social pressure fostered a curious US-USSR backstage collaboration I label leadership capture, decisively shaping the legal compromise embodied in the civilian protection rules of Additional Protocol I to the Geneva Conventions. Theoretically, this article furthers burgeoning IR work on the connection between social pressure, status competition, and international rule-making. Empirically it presents a new archives-based history of an intrinsically important case in international law.</jats:p

Power map permutations and symmetric differences in finite groups

Let $G$ be a finite group. For all $a \in \Z$, such that $(a,|G|)=1$, the function $\rho_a: G \to G$ sending $g$ to $g^a$ defines a permutation of the elements of $G$. Motivated by a recent generalization of Zolotarev's proof of classic quadratic reciprocity, due to Duke and Hopkins, we study the signature of the permutation $\rho_a$. By introducing the group of conjugacy equivariant maps and the symmetric difference method on groups, we exhibit an integer $d_{G}$ such that $\text{sgn}(\rho_a)=(\frac{d_G}{a})$ for all $G$ in a large class of groups, containing all finite nilpotent and odd order groups.Comment: Electronic version of an article to be published as, Journal of Algebra and its Applications, 2011, DOI No: 10.1142/S0219498811005051, \c{opyright} copyright World Scientific Publishing Company, http://www.worldscinet.com/jaa/jaa.shtm

The role of ENSO in understanding changes in Colombia's annual malaria burden by region, 1960–2006

Malaria remains a serious problem in Colombia. The number of malaria cases is governed by multiple climatic and non-climatic factors. Malaria control policies, and climate controls such as rainfall and temperature variations associated with the El Niño/Southern Oscillation (ENSO), have been associated with malaria case numbers. Using historical climate data and annual malaria case number data from 1960 to 2006, statistical models are developed to isolate the effects of climate in each of Colombia's five contrasting geographical regions. Because year to year climate variability associated with ENSO causes interannual variability in malaria case numbers, while changes in population and institutional control policy result in more gradual trends, the chosen predictors in the models are annual indices of the ENSO state (sea surface temperature [SST] in the tropical Pacific Ocean) and time reference indices keyed to two major malaria trends during the study period. Two models were used: a Poisson and a Negative Binomial regression model. Two ENSO indices, two time reference indices, and one dummy variable are chosen as candidate predictors. The analysis was conducted using the five geographical regions to match the similar aggregation used by the National Institute of Health for its official reports. The Negative Binomial regression model is found better suited to the malaria cases in Colombia. Both the trend variables and the ENSO measures are significant predictors of malaria case numbers in Colombia as a whole, and in two of the five regions. A one degree Celsius change in SST (indicating a weak to moderate ENSO event) is seen to translate to an approximate 20% increase in malaria cases, holding other variables constant. Regional differentiation in the role of ENSO in understanding changes in Colombia's annual malaria burden during 1960–2006 was found, constituting a new approach to use ENSO as a significant predictor of the malaria cases in Colombia. These results naturally point to additional needed work: (1) refining the regional and seasonal dependence of climate on the ENSO state, and of malaria on the climate variables; (2) incorporating ENSO-related climate variability into dynamic malaria models

Urban Public Works in Spatial Equilibrium: Experimental Evidence from Ethiopia

This paper evaluates a large urban public works program randomly rolled out across neighborhoods of Addis Ababa, Ethiopia. We find the program increased public employment and reduced private labor supply among beneficiaries and improved local amenities in treated locations. We then combine a spatial equilibrium model and unique commuting data to estimate the spillover effects of the program on private sector wages across neighborhoods: under full program rollout, wages increased by 18.6 percent. Using our model, we show that welfare gains to the poor are six times larger when we include the indirect effects on private wages and local amenities

The JGrass-NewAge system for forecasting and managing the hydrological budgets at the basin scale: models of flow generation and propagation/routing

Abstract. This paper presents a discussion of the predictive capacity of the implementation of the semi-distributed hydrological modeling system JGrass-NewAge. This model focuses on the hydrological budgets of medium scale to large scale basins as the product of the processes at the hillslope scale with the interplay of the river network. The part of the modeling system presented here deals with the: (i) estimation of the space-time structure of precipitation, (ii) estimation of runoff production; (iii) aggregation and propagation of flows in channel; (v) estimation of evapotranspiration; (vi) automatic calibration of the discharge with the method of particle swarming. The system is based on a hillslope-link geometrical partition of the landscape, combining raster and vectorial treatment of hillslope data with vector based tracking of flow in channels. Measured precipitation are spatially interpolated with the use of kriging. Runoff production at each channel link is estimated through a peculiar application of the Hymod model. Routing in channels uses an integrated flow equation and produces discharges at any link end, for any link in the river network. Evapotranspiration is estimated with an implementation of the Priestley-Taylor equation. The model system assembly is calibrated using the particle swarming algorithm. A two year simulation of hourly discharge of the Little Washita (OK, USA) basin is presented and discussed with the support of some classical indices of goodness of fit, and analysis of the residuals. A novelty with respect to traditional hydrological modeling is that each of the elements above, including the preprocessing and the analysis tools, is implemented as a software component, built upon Object Modelling System v3 and jgrasstools prescriptions, that can be cleanly switched in and out at run-time, rather than at compiling time. The possibility of creating different modeling products by the connection of modules with or without the calibration tool, as for instance the case of the present modeling chain, reduces redundancy in programming, promotes collaborative work, enhances the productivity of researchers, and facilitates the search for the optimal modeling solution

Curriculum for Best Practices

Public health professionals, field epidemiologists, health management workers and health policymakers are increasingly concerned about the potential impact that climate can have on public health. Climate not only determines the spatial and seasonal distribution of many public health events, such as infectious diseases, but also is a key determinant of inter-annual variability in disease incidence, including epidemics and medium-term trends. However, many public health professionals are not yet aware of the ways in which climate information can help them manage the impacts of climate on their disease surveillance and control activities, as well as program implementation and evaluation. Similarly, climate scientists are not aware of how they can contribute to the information needs of the public health sector. Despite the challenges inherent to the multidisciplinary nature of the field of climate and public health, interdisciplinary work and dialogue is necessary to bridge this gap. Public health is a broad effort organized by society to protect, promote and restore the people’s health. It is the combination of sciences, skills and beliefs directed to the maintenance and improvement of health through collective or social actions. Many significant contributions to public health stem from activities outside the formal health sector (e.g., water resources management and food security). In this context, climate researchers should be considered a part of the public health community. Protecting public health from the vagaries of climate will requires new working relationships between the public health sector and the providers of climate data and information. It will also demand a wide variety of strategies and must occur at multiple levels. One of these strategies is to increase the public health community’s capacity to understand, use, and demand the appropriate climate information to mitigate the public health impacts of climate. However, good information is not enough. The public health community must also be able to distinguish between different kinds of data to determine what is relevant, at what time and space scale, to their population. Consider, for instance, the many ways that temperature affects human health. Rising average temperatures are predicted to increase the incidence and duration of heat waves, which are known to be a major hazard to particular segments of the population including those with heart problems, respiratory diseases such as asthma, the elderly, the very young, and the homeless. Rising temperatures may also increase the incidence of infectious diseases and contribute to air quality problems. Determining which of these issues are most pressing will require public health professionals to interpret various kinds of information and that is why it is so important to train them. It is also important the courses are tailored to the local context and resources, for developed and developing countries have different abilities to cope with stresses from the climate

2009 Summer Institute on Climate Information for Public Health

As the world’s attention is increasingly focused on the effects of climate change, it is essential to better understand the role that climate plays in community health and disease. Equally important is the need for decisive, coordinated interaction between climate experts and health workers to decide how best to respond to the variations in climate that in part drive the burden of disease in communities of developing countries. The 2009 Summer Institute on Climate Information for Public Health (SI 09) was designed to engage professionals who play a key role in the operational decision-making for climate-sensitive diseases in identifying and evaluating appropriate use of climate information. The International Research Institute for Climate and Society (IRI) designed and implemented the second annual Summer Institute (SI), in partnership with the Center for International Earth Science Information Network (CIESIN) and the Mailman School of Public Health (MSPH) at Columbia University. The IRI is a premier global research and capacity-building institution focused on the use of climate information in key areas of development. It is a collaborating centre with the World Health Organization–Pan-American Health Organization (WHO–PAHO) on climate-sensitive diseases. The IRI, CIESIN, and MSPH are partner institutions of The Earth Institute at Columbia University. Together these institutes combine extensive experience in en- vironmental health, population mapping and modeling with climate prediction and the study of climate variability and change. SI 09 was held at Columbia University’s Lamont-Doherty Campus in Palisades, New York, between June 1st and June 12th, 2009. A panel discussion was held at the MSPH on June 3rd, 2009