Shades of CORDS in the Kush : the false hope of "unity of effort" in American counterinsurgency /

"Counterinsurgency (COIN) requires an integrated military, political, and economic program best developed by teams that field both civilians and soldiers. These units should operate with some independence but under a coherent command. In Vietnam, after several false starts, the United States developed an effective unified organization, Civil Operations and Revolutionary Development Support (CORDS), to guide the counterinsurgency. CORDS had three components absent from our efforts in Afghanistan today: sufficient personnel (particularly civilian), numerous teams, and a single chain of command that united the separate COIN programs of the disparate American departments at the district, provincial, regional, and national levels. This paper focuses on the third issue and describes the benefits that unity of command at every level would bring to the American war in Afghanistan. The work begins with a brief introduction to counterinsurgency theory, using a population-centric model, and examines how this warfare challenges the United States. It traces the evolution of the Provincial Reconstruction Teams (PRTs) and the country team, describing problems at both levels. Similar efforts in Vietnam are compared, where persistent executive attention finally integrated the government's counterinsurgency campaign under the unified command of the CORDS program. The next section attributes the American tendency towards a segregated response to cultural differences between the primary departments, executive neglect, and societal concepts of war. The paper argues that, in its approach to COIN, the United States has forsaken the military concept of unity of command in favor of 'unity of effort' expressed in multiagency literature. The final sections describe how unified authority would improve our efforts in Afghanistan and propose a model for the future."--P. iii.

Emmenologie, ou Traite de l'evacuation ordinaire aux femmes : ou l'on explique les phénomenes, les retours ... /

Mode of access: Internet.

American soldiers and Chinese civilians sitting at banquet table.

On verso: Passed for publication U.S. Army Press censor. Lt. Mark M. Barkan 61206,China-Burma-India. CBI-44 60665

Tracing Hybrid Collectives of Illness, War, and Medicine in Twentieth- and Twenty-First Century Narratives of Illness

Thesis (Ph.D.)--University of Washington, 2016-06

Disseminating a warning message to evacuate:a simulation study of the behaviour of neighbours

Large-scale evacuations are a recurring theme on news channels, whether in response to major natural or manmade disasters. The role of warning dissemination is a key part in the success of such large-scale evacuations and its inadequacy in certain cases has been a 'primary contribution to deaths and injuries' (Hayden et al.; 2007). Along with technology-driven 'official warning channels' (e.g. sirens, mass media), the role of unofficial channel (e.g. neighbours, personal contacts, volunteer wardens) has proven to be significant in warning the public of the need to evacuate. Although post-evacuation studies identify the behaviours of evacuees as disseminators of the warning message, there has not been a detailed study that quantifies the effects of such behaviour on the warning message dissemination. This paper develops an Agent-Based Simulation (ABS) model of multiple agents (evacuee households) in a hypothetical community to investigate the impact of behaviour as an unofficial channel on the overall warning dissemination. Parameters studied include the percentage of people who warn their neighbours, the efficiency of different official warning channels, and delay time to warn neighbours. Even with a low proportion of people willing to warn their neighbour, the results showed considerable impact on the overall warning dissemination. © 2012 Elsevier B.V. All rights reserved.

Analyzing evacuation decisions using multi-attribute utility theory (MAUT)

Emergency managers are faced with critical evacuation decisions. These decisions must balance conflicting objectives as well as high levels of uncertainty. Multi-Attribute Utility Theory (MAUT) provides a framework through which objective trade-offs can be analyzed to make optimal evacuation decisions. This paper is the result of data gathered during the European Commission Project, Evacuation Responsiveness by Government Organizations (ERGO) and outlines a preliminary decision model for the evacuation decision. The illustrative model identifies levels of risk at which point evacuation actions should be taken by emergency managers in a storm surge scenario with forecasts at 12 and 9 hour intervals. The results illustrate how differences in forecast precision affect the optimal evacuation decision. Additional uses for this decision model are also discussed along with improvements to the model through future ERGO data-gathering.

A multi-organisational approach for disaster preparedness and response:the use of optimisation and GIS for facility location, stock pre-positioning, resource allocation and relief distribution

From 1992 to 2012 4.4 billion people were affected by disasters with almost 2 trillion USD in damages and 1.3 million people killed worldwide. The increasing threat of disasters stresses the need to provide solutions for the challenges faced by disaster managers, such as the logistical deployment of resources required to provide relief to victims. The location of emergency facilities, stock prepositioning, evacuation, inventory management, resource allocation, and relief distribution have been identified to directly impact the relief provided to victims during the disaster. Managing appropriately these factors is critical to reduce suffering. Disaster management commonly attracts several organisations working alongside each other and sharing resources to cope with the emergency. Coordinating these agencies is a complex task but there is little research considering multiple organisations, and none actually optimising the number of actors required to avoid shortages and convergence. The aim of the this research is to develop a system for disaster management based on a combination of optimisation techniques and geographical information systems (GIS) to aid multi-organisational decision-making. An integrated decision system was created comprising a cartographic model implemented in GIS to discard floodable facilities, combined with two models focused on optimising the decisions regarding location of emergency facilities, stock prepositioning, the allocation of resources and relief distribution, along with the number of actors required to perform these activities. Three in-depth case studies in Mexico were studied gathering information from different organisations. The cartographic model proved to reduce the risk to select unsuitable facilities. The preparedness and response models showed the capacity to optimise the decisions and the number of organisations required for logistical activities, pointing towards an excess of actors involved in all cases. The system as a whole demonstrated its capacity to provide integrated support for disaster preparedness and response, along with the existence of room for improvement for Mexican organisations in flood management.

Essays in environmental economic valuation and decision making in the presence of an environmental disaster

The first essay developed a respondent model of Bayesian updating for a double-bound dichotomous choice (DB-DC) contingent valuation methodology. I demonstrated by way of data simulations that current DB-DC identifications of true willingness-to-pay (WTP) may often fail given this respondent Bayesian updating context. Further simulations demonstrated that a simple extension of current DB-DC identifications derived explicitly from the Bayesian updating behavioral model can correct for much of the WTP bias. Additional results provided caution to viewing respondents as acting strategically toward the second bid. Finally, an empirical application confirmed the simulation outcomes. The second essay applied a hedonic property value model to a unique water quality (WQ) dataset for a year-round, urban, and coastal housing market in South Florida, and found evidence that various WQ measures affect waterfront housing prices in this setting. However, the results indicated that this relationship is not consistent across any of the six particular WQ variables used, and is furthermore dependent upon the specific descriptive statistic employed to represent the WQ measure in the empirical analysis. These results continue to underscore the need to better understand both the WQ measure and its statistical form homebuyers use in making their purchase decision. The third essay addressed a limitation to existing hurricane evacuation modeling aspects by developing a dynamic model of hurricane evacuation behavior. A household's evacuation decision was framed as an optimal stopping problem where every potential evacuation time period prior to the actual hurricane landfall, the household's optimal choice is to either evacuate, or to wait one more time period for a revised hurricane forecast. A hypothetical two-period model of evacuation and a realistic multi-period model of evacuation that incorporates actual forecast and evacuation cost data for my designated Gulf of Mexico region were developed for the dynamic analysis. Results from the multi-period model were calibrated with existing evacuation timing data from a number of hurricanes. Given the calibrated dynamic framework, a number of policy questions that plausibly affect the timing of household evacuations were analyzed, and a deeper understanding of existing empirical outcomes in regard to the timing of the evacuation decision was achieved.

Predicting hurricane evacuation decisions: When, how many, and how far

Traffic from major hurricane evacuations is known to cause severe gridlocks on evacuation routes. Better prediction of the expected amount of evacuation traffic is needed to improve the decision-making process for the required evacuation routes and possible deployment of special traffic operations, such as contraflow. The objective of this dissertation is to develop prediction models to predict the number of daily trips and the evacuation distance during a hurricane evacuation. ^ Two data sets from the surveys of the evacuees from Hurricanes Katrina and Ivan were used in the models' development. The data sets included detailed information on the evacuees, including their evacuation days, evacuation distance, distance to the hurricane location, and their associated socioeconomic characteristics, including gender, age, race, household size, rental status, income, and education level. ^ Three prediction models were developed. The evacuation trip and rate models were developed using logistic regression. Together, they were used to predict the number of daily trips generated before hurricane landfall. These daily predictions allowed for more detailed planning over the traditional models, which predicted the total number of trips generated from an entire evacuation. A third model developed attempted to predict the evacuation distance using Geographically Weighted Regression (GWR), which was able to account for the spatial variations found among the different evacuation areas, in terms of impacts from the model predictors. All three models were developed using the survey data set from Hurricane Katrina and then evaluated using the survey data set from Hurricane Ivan. ^ All of the models developed provided logical results. The logistic models showed that larger households with people under age six were more likely to evacuate than smaller households. The GWR-based evacuation distance model showed that the household with children under age six, income, and proximity of household to hurricane path, all had an impact on the evacuation distances. While the models were found to provide logical results, it was recognized that they were calibrated and evaluated with relatively limited survey data. The models can be refined with additional data from future hurricane surveys, including additional variables, such as the time of day of the evacuation. ^

Essays in Environmental Economic Valuation and Decision Making in the Presence of an Environmental Disaster

The first essay developed a respondent model of Bayesian updating for a double-bound dichotomous choice (DB-DC) contingent valuation methodology. I demonstrated by way of data simulations that current DB-DC identifications of true willingness-to-pay (WTP) may often fail given this respondent Bayesian updating context. Further simulations demonstrated that a simple extension of current DB-DC identifications derived explicitly from the Bayesian updating behavioral model can correct for much of the WTP bias. Additional results provided caution to viewing respondents as acting strategically toward the second bid. Finally, an empirical application confirmed the simulation outcomes. The second essay applied a hedonic property value model to a unique water quality (WQ) dataset for a year-round, urban, and coastal housing market in South Florida, and found evidence that various WQ measures affect waterfront housing prices in this setting. However, the results indicated that this relationship is not consistent across any of the six particular WQ variables used, and is furthermore dependent upon the specific descriptive statistic employed to represent the WQ measure in the empirical analysis. These results continue to underscore the need to better understand both the WQ measure and its statistical form homebuyers use in making their purchase decision. The third essay addressed a limitation to existing hurricane evacuation modeling aspects by developing a dynamic model of hurricane evacuation behavior. A household’s evacuation decision was framed as an optimal stopping problem where every potential evacuation time period prior to the actual hurricane landfall, the household’s optimal choice is to either evacuate, or to wait one more time period for a revised hurricane forecast. A hypothetical two-period model of evacuation and a realistic multi-period model of evacuation that incorporates actual forecast and evacuation cost data for my designated Gulf of Mexico region were developed for the dynamic analysis. Results from the multi-period model were calibrated with existing evacuation timing data from a number of hurricanes. Given the calibrated dynamic framework, a number of policy questions that plausibly affect the timing of household evacuations were analyzed, and a deeper understanding of existing empirical outcomes in regard to the timing of the evacuation decision was achieved.

A philosophy of performance, politics and composition

This thesis discusses socio-political issues worldwide through philosophical approaches to performance, politics and composition. My research also discuss sound decisions which I regard to be simultaneously an outlet for personal expression, as well as a practical tool to inspire a socio-political change in society. Although the latter is paramount to the methodology of the project, the sound cannot be regarded in isolation as a “political composition”. It can only become truly functional in a political sense through interaction with other art forms, within the context of a specific place and time. My portfolio for this project is of two socio-political projects which are my chief concern. The first project concerns the Israeli-Palestinian conflict. I named this project PATH. PATH aims to foster and expand peaceful thought between Jewish and Palestinian civilians in Israel-Palestine. Through performance art, PATH spreads a message of acceptance, unity and brotherhood between our peoples. Above all, PATH demands and end to intolerance, hatred and violence among all the inhabitants of the State of Israel. The second project concerns women’s rights globally. I have realised that although we have come a long way in our struggle for rights for women, great challenges remain. There is a need to unite women and men against a form of oppression that discriminates against 50% of the world’s population. I called this project, For Utopia.

Governmentality and exclusion in post-disaster spaces : conducting the conduct of the survivors of Typhoon Sendong in Cagayan de Oro, Philippines

Lorsque les aléas naturels se déroulent en catastrophes, les réponses des religieux, de l’Etat, et d’autres acteurs puissants dans une société révèlent à la fois les relations complexes entre ces parties et leur pouvoir dans la production des espaces auxquelles les survivants accèdent. La réponse en cas de catastrophe comprend la création d’espaces post-catastrophes, tels que des centres d’évacuation, des logements de transition et des sites de réinstallation permanente, qui ciblent spécifiquement un sous-ensemble particulier de survivants, et visent à les aider à survivre, à faire face, et à se remettre de la catastrophe. Les acteurs puissants dans une société dirigent les processus de secours, de récupération et de reconstruction sont des acteurs puissants qui cherchent à problématiser et à rendre un problème technique dans des termes qu’ils sont idéalement placés pour aborder à travers une variété d'interventions. Ce projet de recherche vise à répondre à la question: où les survivants d'une catastrophe reconstruisent-ils leurs vies et leurs moyens de subsistance? Il enquête sur un cas spécifique de la migration environnementale dans laquelle des dizaines de milliers d'habitants ont été déplacés de façon permanente et temporaire de leurs résidences habituelles après le typhon Sendong à Cagayan de Oro, Philippines en 2011. La recherche est basée sur des entretiens avec les acteurs puissants et les survivants, des vidéos participatives réalisées par des survivants pauvres urbains, et des activités de cartographie. L’étude se fonde sur la théorie féministe, les études de migration, les études dans la gouvernementalité, la recherche sur les changements de l’environnement planétaire, et les études régionales afin de situer les diverses expériences de la migration dans un contexte géographique et historique. Cette thèse propose une topographie critique dans laquelle les processus et les pratiques de production d’espaces post-catastrophe sont exposés. Parce que l’espace est nécessairement malléable, fluide, et relationnelle en raison de l'évolution constante des activités, des conflits, et des expériences qui se déroulent dans le paysage, une analyse de l'espace doit être formulée en termes de relations sociales qui se produisent dans et au-delà de ses frontières poreuses. En conséquence, cette étude explore comment les relations sociales entre les survivants et les acteurs puissants sont liées à l’exclusion, la gouvernementalité, la mobilité, et la production des espaces, des lieux et des territoires. Il constate que, si les trajectoires de migration de la plupart des survivants ont été confinés à l'intérieur des limites de la ville, les expériences de ces survivants et leur utilisation des espaces urbains sont très différentes. Ces différences peuvent être expliquées par des structures politiques, économiques, et sociales, et par les différences religieuses, économiques, et de genre. En outre, il fait valoir que les espaces post-catastrophe doivent être considérés comme des «espaces d’exclusion» où les fiduciaires exercent une rationalité gouvernementale. C’est-à-dire, les espaces post-catastrophe prétendument inclusives servent à marginaliser davantage les populations vulnérables. Ces espaces offrent aussi des occasions pour les acteurs puissants dans la société philippine d'effectuer des interventions gouvernementales dans lesquelles certaines personnes et les paysages sont simplifiées, rendues lisibles, et améliorés.

Endogenous Risk Perception, Geospatial Characteristics and Temporal Variation in Hurricane Evacuation Behavior

The main focus of this thesis was to gain a better understanding about the dynamics of risk perception and its influence on people’s evacuation behavior. Another major focus was to improve our knowledge regarding geo-spatial and temporal variations of risk perception and hurricane evacuation behavior. A longitudinal dataset of more than eight hundred households were collected following two major hurricane events, Ivan and Katrina. The longitudinal survey data was geocoded and a geo-spatial database was integrated to it. The geospatial database was composed of distance, elevation and hazard parameters with respect to the respondent’s household location. A set of Bivariate Probit (BP) model suggests that geospatial variables have had significant influences in explaining hurricane risk perception and evacuation behavior during both hurricanes. The findings also indicated that people made their evacuation decision in coherence with their risk perception. In addition, people updated their hurricane evacuation decision in a subsequent similar event.