Building and Using Datasets on Armed Conflicts (Nato Science for Peace and Security) (Nato Science for Peace and Security)

BUILDING AND USING DATASETS ON ARMED CONFLICTS

NATO Science for Peace and Security Series This Series presents the results of scientific meetings supported under the NATO Programme: Science for Peace and Security (SPS). The NATO SPS Programme supports meetings in the following Key Priority areas: (1) Defence Against Terrorism; (2) Countering other Threats to Security and (3) NATO, Partner and Mediterranean Dialogue Country Priorities. The types of meeting supported are generally “Advanced Study Institutes” and “Advanced Research Workshops”. The NATO SPS Series collects together the results of these meetings. The meetings are co-organized by scientists from NATO countries and scientists from NATO’s “Partner” or “Mediterranean Dialogue” countries. The observations and recommendations made at the meetings, as well as the contents of the volumes in the Series, reflect those of participants and contributors only; they should not necessarily be regarded as reflecting NATO views or policy. Advanced Study Institutes (ASI) are high-level tutorial courses to convey the latest developments in a subject to an advanced-level audience. Advanced Research Workshops (ARW) are expert meetings where an intense but informal exchange of views at the frontiers of a subject aims at identifying directions for future action. Following a transformation of the programme in 2006 the Series has been re-named and reorganised. Recent volumes on topics not related to security, which result from meetings supported under the programme earlier, may be found in the NATO Science Series. The Series is published by IOS Press, Amsterdam, and Springer Science and Business Media, Dordrecht, in conjunction with the NATO Public Diplomacy Division. Sub-Series A. B. C. D. E.

Chemistry and Biology Physics and Biophysics Environmental Security Information and Communication Security Human and Societal Dynamics

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Sub-Series E: Human and Societal Dynamics – Vol. 36

ISSN 1874-6276

Building and Using Datasets on Armed Conflicts

Edited by

Mayeul Kauffmann École de la paix, Grenoble, France

Amsterdam • Berlin • Oxford • Tokyo • Washington, DC Published in cooperation with NATO Public Diplomacy Division

Proceedings of the NATO Advanced Research Workshop on Indicators and Databases for Risk Prevention Grenoble, France 21–23 June 2007

© 2008 IOS Press. All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, without prior written permission from the publisher. ISBN 978-1-58603-847-2 Library of Congress Control Number: 2008922611 Publisher IOS Press Nieuwe Hemweg 6B 1013 BG Amsterdam Netherlands fax: +31 20 687 0019 e-mail: [email protected] Distributor in the UK and Ireland Gazelle Books Services Ltd. White Cross Mills Hightown Lancaster LA1 4XS United Kingdom fax: +44 1524 63232 e-mail: [email protected]

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Building and Using Datasets on Armed Conflicts M. Kauffmann (Ed.) IOS Press, 2008 © 2008 IOS Press. All rights reserved.

v

Preface Richard PÉTRIS Director, École de la paix, Grenoble The so-called “hard” or “exact” sciences, with their necessary emphasis on technology and on the technical, are hardly reputed for being very human, and, conversely, the socalled “human” sciences are often pronounced as “soft” because they cannot be based on the certainties associated with the former. The search for truth which is the essential dimension of the construction of a peaceful world therefore has to navigate between considerations of a philosophical nature and the concrete data of the hard sciences. If, ever since the humanism of the Renaissance period, we have been happy to lay claim to the wisdom of one of its great writers, Rabelais, who taught a moral lesson to the young Pantagruel with the neat formula “science without conscience is the ruin of the soul”, we nonetheless stand in awe before modern scientific advances and the extraordinary achievements that they have opened up. If everything is not permissible, at least everything seems possible! It was such an outlook which no doubt had something to do with our decision taken ten years ago here in Grenoble to give concrete shape to a utopian dream by creating in our city a “school for peace”. At that time we were reminded that a Brazilian bishop, Don Helder Camara, famous for the stands which he took in favour of human development and the promotion of peace through dialogue and a more just distribution of resources, had once remarked that Grenoble would be an ideal place to combine its advanced technological and computing research with the philosophical and humanist dimension to bring about the necessary synthesis for the promotion of the cause of peace in the world. And he had made this comment at the height of the cold war, as a way of confronting and fighting against the extremism that posed such a threat at that time. Since then, the Third World War has not happened and if one can pose the question of why the North Atlantic Treaty Organisation should be maintained, an organisation which without a doubt contributed to the prevention of such a war, we should not ignore the threats and challenges which remain, or are even greater today, in the general field of world security. This is why we were very gratified when we realised that an Alliance, which some felt was the product of a bygone age, was reorienting its scientific programme in order to “favour research on questions linked to security and by so doing to better reflect the new environment in which NATO finds itself”. And that in order to face the complex questions associated with security, there would be “a greater interaction between the exact sciences and the human and social sciences”. By submitting a project to hold an Advanced Research Workshop on the theme of “indicators and databases for risk prevention”, we gave ourselves the chance to deepen and prolong research which we were already engaged in, based on the idea that a climate or a culture of peace needed to be encouraged and that there were effective ways in which progress could be made in this domain. We believe that this area of study can be subjected to measurement and quanti-

vi

fication. We are now equipped with measuring instruments for natural phenomena, and in a world of increasing complexity, we are more and more concerned with questions of efficiency, of performance and evaluation in all domains, including those which are related to questions concerning the quality of life and the avoidance of social conflict. Comments on war are now inevitably accompanied by sets of “figures” concerning the loss of human lives and the “collateral damage”—all sorts of damage which come in its wake. To the sinister “body count” of open and full war, we must add the information concerning the horrors of all other forms of violence and ignored wars, if our intention is to take the real measure of human tragedies which they entail in order to awaken public conscience and encourage appropriate political action. But we must also today take into account the figures and statistics of new fields of research and action, concerning the environment and sustainable development, if there is going to be real progress on global prevention. The human development indicators of the United Nations Development Programme (UNDP) seem to us to show the way forward in this respect. Furthermore, we support the recommendation of the mathematician, historian and philosopher, Michel Serres, when he says “Since we control the whole world, we must learn to control our own control mechanisms” and we also share the belief of Martin Hirsch, president of the humanitarian organisation Emmaüs, who, just before taking up his French governmental appointment, declared on the subject of poverty indicators: “They are indispensable… To try to do without them would be like tackling road safety, without using devices for measuring and registering speed!” We were therefore clearly aware that all sorts of research is being undertaken in this vast domain and the time had come to bring it all together and submit it to further empirical evidence. All the actors concerned, the politicians, diplomats, the military, the NGOs, as well as the heads of enterprise, need a clearer vision of the state of a world which is more and more complex. The improvement of our information systems is therefore particularly useful, both for pure research and for its applications. The sharing of means and techniques of information, the development of “synthetic” coordinated indicators and even the identification of new data which will help with risk analysis and conflict prevention in tomorrow’s world, all these constituted the agenda for this Advanced Research Workshop. Our approach was to give as much freedom as possible to specialists in presenting their work, so that new ways forward and approaches could be identified and facilitated. The aim of this publication is to render account as faithfully as possible of the diversity of approaches taken by the 27 researchers and experts from 13 countries who participated in this Advanced Research Workshop. It will of course take time to evaluate the potential for progress in all this but these two figures point the way forward.

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Foreword Ranan D. KUPERMAN University of Haifa 1. Why Are Datasets Needed? The simplest reason why data is collected and stored, thereby creating a dataset, is to aggregate this information in order to measure performance over time [1–3]. A slightly more sophisticated use of a dataset is to try and explore the relationship between different measures, thereby discovering casual effects. Finally a third application of a dataset is using it as a source of reference. In this case, the user of the dataset seeks to identify specific cases for further analysis according to some criteria that have been classified by the creator of the database. The use of datasets in order to study the development of peace and conflict started in the 1940s with Richardson’s work on deadly quarrels [4] and Wright’s work on the causes of war [5]. In this case the tendency to create datasets could be attributed to the behavioral revolution in the social sciences during the 20th century, which encouraged large sample comparisons and quantitative forms of analysis. However, even after the demise of the behavioral movement, the tendency to collect and accumulate data seems to have only increased. This is most probably attributable to the expansion of low cost computerized systems. Thus, the creation of electronic datasets related to conflict and cooperation has become a relatively simple enterprise, and many organizations consistently engage in various forms of data collection related to conflicts.

2. Why Should Datasets Be Shared? Another advantage of the significant developments in computer technology is that the ability to transfer data has become relatively cheap and fast. Thus, there is a high demand to share datasets and thereby save time and resources duplicating previous work. However, sharing data has other objectives as well. It allows researchers to compare alternative collections of data [6,7], which in turn can indicate the reliability or validity of data collections. Large discrepancies between datasets coding similar events, indicates that at least one of them has been poorly coded. Frequently these variations are due to different interpretations of the raw data (in its original format before it was coded) or relying on different sources. In these cases, it is possible to fill in missing data and thus improve the validity of the dataset.

3. Improving the Validity of Datasets It seems that the demand for security related datasets is growing. This trend will most probably be accompanied with a demand to strengthen the quality of the data. In order to improve the validity of the datasets two procedures are suggested.

viii

The first relates to the quality of the raw material that is used in order to produce the data. Rather than relying solely on the reports of major newspapers or news agencies, data should be sought from sources that have better access to information, such as archived material and foreign language reports, and possibly even through direct contacts with local observers [8]. The second procedure relates to the integration of information from alternative sources. Standards regarding the validity of the sources will be required. Such a measure is especially necessary when there is a conflict between information from different sources. Many researchers circumvent this issue by coding both interpretations rather than making a decision in favor of one source. This allows the user of the dataset to decide which interpretation to accept. However, frequently datasets do not display information about the sources of the raw data and therefore the user has no criteria that can be used in order to decide which interpretation to prefer. It is thus suggested that datasets include full information about their sources. An alternative possibility is that the coders of the dataset determine themselves which source should be preferred. In this case, the coders must provide a detailed account of the criteria that was applied in order to accept or reject information (for an example see [9]).

4. Improving Our Ability to Share Datasets A second set of improvements is required in order to encourage the sharing of datasets. Essentially this requires the creators of datasets to think about establishing universal coding procedures. Because there are currently no agreed upon standards for classifying and categorizing data, comparing data between alternative datasets for the purpose of cross referencing or reducing missing data is not reliable [10]. Unless the coding procedures are identical, attempting to combine or compare data between alternatives sets may lead to considerable errors. This problem could partially be overcome if instead of coding for very specific types of variables, variables would be disaggregated into a number of subtypes. This approach was in fact adopted during the early coding of events datasets such as the Conflict and Peace Data Bank (COPDAB) or World Event/Interaction Survey (WEIS) and in a similar manner there have been attempts to combine the two datasets together [11]. However, because it is very difficult to maintain funding for generating general cooperation and conflict datasets, such a breakdown of variables into subcategories is not encouraged. Even when the group funding the dataset has a specific agenda, breaking down the variables into sub-categories should not consist of significant extra work and therefore should be encouraged. In addition, it is advisable to consider adding to datasets a copy of the original textual source. This can also be used in order to account for coding differences between alternative datasets. Besides dealing with coding procedures another important aspect of sharing data is accessibility. Many datasets cannot be easily downloaded from the Internet and the owners of the datasets are frequently reluctant to share their data. In recent years a number of scientific journals have started demanding as a precondition for publication that the authors make their data available. It is hereby suggested that also organizations providing grants for the creation of datasets adopt this policy. Yet even if datasets are available, researchers must know that the dataset exists and how to obtain it. Although there are a number of Internet sites that provide this information, such as at PRIO or ICPSR, there is preference to direct researchers to datasets that were compiled by aca-

ix

demics or governmental agencies. However, in reality there are many more datasets that are compiled by various NGOs and think tanks that can also be used. Thus, a more comprehensive index of alternative datasets is required. In addition to the description of what type of data is stored within each dataset, dataset indexes should also include information regarding the validity and reliability of these datasets, meaning what were the sources that were relied upon in order to code events, and what if at all were the coding procedures.

5. Establishing the Foundations of a Paradigm To a great extent the creation and maintenance of datasets can be viewed as a profession. Many organizations usually recruit a person who will be responsible for designing, coding, and maintaining their databases. Frequently this person is chosen on the basis of technical capabilities rather than research experience. In order to overcome this person’s lack of research skills a senior researcher is also assigned to oversee the maintenance of the dataset. However, it is very common that tensions start emerging between the managers of the dataset. Such a scenario will usually occur if the senior researcher fails to actually analyze and negotiate the raw data. Thus, persons compiling the data are confronted with many dilemmas regarding how to code the data because the classifications proposed by the senior researchers seem to be irrelevant to the actual information that is being reviewed. The coders might even fail to compile important data when the senior researcher is not even aware of its existence. Overcoming these problems requires the accumulation of experience. Yet it seems that these issues remain hidden and unrecorded. Another example where experience is not redistributed is the discovery of errors within existing datasets. This information remains out of sight and restricted to personal knowledge and therefore, many errors that researchers find in their datasets are not reported to other researchers who use the same datasets. Unfortunately it seems that each time a new research project that relies on the use of data analysis is launched the research team is destined to repeat the mistakes of previous researchers. In this respect, data analysts in the field of conflict and cooperation must pay more attention to the special and unique problems associated with the coding of datasets. There seems to be an overemphasis on developing statistical methodological issues, while very little concern about how the data that is used in these procedures is produced. Therefore, dataset managers should establish a forum for exchanging professional information with each other. Such a forum could serve as the basis for standardizing this field, and thereby a new generation of dataset managers will be able to build on their predecessors experiences and possibly devote more energy to solving problems and dilemmas that still remain.

References [1] Caplow, Theodore (1976). How to Run Any Organization. New York: Holt, Rinehart and Winston. [2] Rossi, Robert J. and Kevin J. Gilmartin (1980). The Handbook of Social Indicators: Sources, Characteristics, and Analysis. New York: Garland STPM Press. [3] Taylor, Charles Lewis [ed.] (1980), Indicator Systems for Political, Economic, and Social Analysis. Cambridge, MA: Oelgeschlager, Gunn & Hain.

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[4] Richardson, Lewis F. (1948). “Variation of the Frequency of Fatal Quarrels with Magnitude”, Journal of the American Statistical Association, 244: 523-546. [5] Wright, Quincy (1944 [1942]), A Study of War. Chicago: University of Chicago Press. [6] Hoggard, Gary D. (1975). “An Analysis of ‘Real’ Data: Reflection on the Uses and Validity of International Interaction Data.” In Theory and Practice of Events Research: Studies on Inter-Nation Actions and Interactions. Edited by E.E. Azar, J.D. Ben-Dak and P.M. Burgess, pp. 19-27. New York: Gordon and Breach Science Publishers. [7] Reuveny, Rafael and Heejoon Kang (1996). “International Conflict and Cooperation: Splicing COPDAB and WEIS Series.” International Studies Quarterly, 40(2): 281-305. [8] SwissPeace, “Early Warning, About”. Available at http://www.swisspeace.ch/typo3/en/peace-conflictresearch/early-warning/about/index.html, accessed on 17 December 2007. [9] Kuperman, Ranan D. (2001). “Rules of Military Retaliation and their Practice by the State of Israel,” International Interactions, 25(3): 1-36. [10] McClelland, Charles A. (1983). “Let the User Beware.” International Studies Quarterly, 27(2): 169177. [11] Ward, Michael D. and Sheen Rajmaira (1992). “Reciprocity and Norms in U.S.-Soviet Foreign Policy”, The Journal of Conflict Resolution, 36(2): 342-368.

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Contents Preface Richard Pétris Foreword Ranan D. Kuperman Introduction Mayeul Kauffmann

v vii

1

The Purposes of Conflict Dataset Building The Creation and Use of Data: Scientific Requirements and Political Utility Wolf-Dieter Eberwein

13

An Overview and Typology of Conflict Data: The Advantages of Data Diversity Kristine Eck

29

Databases on Defense for Influencing State Policies Jean-Marie Collin

41

Concept Definition and Data Building Calling a Conflict a Conflict: Violence and Other Aspects of War Joakim Kreutz

49

Databases on Terrorism: Constructing a Database on Hostage-Barricade Terrorism and Abductions Galit M. Ben-Israel

63

Reviewing CIDCM Databases: Modeling and Indicator Development in Risk Assessments and Early Warnings Lyubov Mincheva

75

Indexes for Measures of Conflict and Cooperation Ranan D. Kuperman

97

Opening up Conflict Data Enhancing Openness and Reliability in Conflict Dataset Creation Mayeul Kauffmann

107

Merging and Meshing Data: Difficulties, Lessons, and Suggestions D. Scott Bennett

133

The ACLED Data Project: Purpose and Methods Clionadh Raleigh and Joachim Carlsen

161

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Visualization of Conflict Networks Ulrik Brandes and Jürgen Lerner

169

Author Index

189

Building and Using Datasets on Armed Conflicts M. Kauffmann (Ed.) IOS Press, 2008 © 2008 IOS Press. All rights reserved.

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Concept Definition and Data Building

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Building and Using Datasets on Armed Conflicts M. Kauffmann (Ed.) IOS Press, 2008 © 2008 IOS Press. All rights reserved.

49

Calling a Conflict a Conflict: Violence and Other Aspects of War Joakim KREUTZ Uppsala Conflict Data Program, Uppsala University, Sweden

Abstract. Arguably the most important aspect for researchers and policymakers is to have access to reliable information, especially when focusing on armed conflict. In order to know when there is greater risk for the outbreak of war, whether containment has been effective, or when post-conflict measures are appropriate, there is a need to clarify what an armed conflict consists of. The most commonly employed definitions of armed conflict are being measured through battle-related fatalities tied to the political goals of the warring sides. This definition excludes several other indicators of human suffering, such as violent crime, genocide, starvation, and forced migration. This chapter reviews some of the problems with expanding the concept of conflict and argues that it is beneficial to use a narrow conflict concept in order to study the relationship between war and other phenomena such as criminality and genocide. Keywords. Crime, violence, indirect deaths, war deaths, genocide.

Introduction The study of war has a long tradition, particularly among historians and military strategists, but also within the social sciences. Carl von Clausewitz’s dictum that “war is the continuation of politics by other means” emphasises the use of violence as the ultimate means in the quest for power or control over a territory. Following the behavioural revolution in the social sciences after World War II, it was argued that the occurrence of war could be explained as a repetitive pattern originating in basic and observable conditions, i.e. each event is not unique. These views formed the theoretical framework for the first conflict data projects. One such project was the Correlates of War (COW), which collected information on conflicts and also other key variables that could explain (or “correlate with”) the outbreak of war including iron and steel production, demographic data, diplomatic linkages, etc. [1]. The original intent of conflict data researchers was to explore why wars begin. The scope soon widened to also focus on why, and how, wars end. These two main questions guided the development of the academic definitions of war, as it was necessary to distinguish the concept as separate phenomenon with identifiable start and end-dates. In practice, war became defined as a contest between organized groups, at least one of which was the government of a state, with political goals, and where violent acts between the groups reached a certain severity threshold. The COW definition of war requiring at least 1,000 battle-deaths in a year became so widely accepted that when other projects started coding organized violence with fewer fatalities these were not referred to as alternative definitions of war, but as “minor

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J. Kreutz / Calling a Conflict a Conflict: Violence and Other Aspects of War

armed conflicts” (Uppsala Conflict Data Program, UCDP), “disputes” (Militarized Interstate Disputes, MID), or “crises” (International Crisis Behaviour, ICB). Information on events during conflicts was less in demand and remained largely the topic for studies on military strategy or the anthropology of violence. An outlook that changed in the 1990s when policymakers, activists, and political scientists became increasingly concerned with an alleged era of “new wars” [2]. These, it was argued, were intrastate rather than interstate, more violent, fought for economic rather than political gain, and not fought in battles but consisted of attacks on defence-less civilians. The “new wars” argument was often accompanied by a growing scepticism, mainly from the policy community, towards the established conflict data projects as it suggested that the conflict data approach to defining war misrepresented the severity of armed conflict [3]. Since the end of the Cold War and the changes in the international system that followed, it is clear that there is a need to review and contemplate the definitions of war that are employed in conflict data research. The latest war between states registered by the UCDP ended on 26 November 2003 when India and Pakistan agreed to a ceasefire, but there was still some 32 intrastate conflicts active in 2006. This paper will not attempt to comment on the “new wars” argumentation as this has been done elsewhere [4], but instead to consider some of the suggestions for changing the definition of war. In order to study changes in the phenomenon of political violence, it is of great importance to resist the temptation of manipulating the definition of war. Expanding the definition to include other events will limit the analytical clarity of the concept and lead to less useful research findings to guide policymakers. As conflict data projects become ever better at providing detailed information on different aspects of war, the need for clear and consistent definitions increases. Without stringent definitions, it will not be possible to increase our knowledge of the causal relationships between: direct and indirect conflict deaths, conflict and genocide, or conflict and crime. Thus the challenge is not primarily in changing our understanding of war, but of identifying and systematically study other phenomenon that often, although not exclusively, can be found simultaneously as an armed conflict.

1. Non-lethal Measures of the Severity of Conflict In order to understand trends in warfare across time and space, it is necessary to develop some kind of measure for the severity of a conflict. Traditionally, conflict data projects have focused on the number of fatalities reported in a year but this may not be the most appropriate measure. If the aim is to fully understand the impact a conflict has on a society, there are many indicators that arguably are more useful, such as the number of violent incidents, number of injured, or number of refugees. These measures could be used as indicators of the immediate impact as well as the long-term consequences of the severity of conflict. 1.1. Incidents as a Measure of the Severity of Conflict Attacks on infrastructure or economic centres can have more impact on a society than the use of armed force that lead to some casualties. Furthermore, non-lethal attacks also send a strong message that can be used to challenge or undermine the authority of a

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51

government. The Colombian anti-government group M-19 initially focused on highpublicity operations, so-called “golpe revolucionario publicitario”, to create civil disorder. Their first operation consisted of stealing the sword of the national hero Simon Bolivár from its exhibition in Bogotá in 1974, an attack that did not lead to any casualties but had significant political effects in Colombia [5]. Another important effect of a large number of incidents, even if these are non-lethal, is the ability to interrupt the normality and create fear among the population. This is a concept that has been embraced in the growing research agenda on terrorism, where systematic data is collected on incidents rather than fatalities. Arguably the main challenge for this field of study is the lack of a coherent universal definition of what terrorism constitutes, even though the emphasis has become the intent of actors to produce fear for sociopolitical purposes [6]. The focus on incidents is an interesting approach to measuring the severity of conflict, but it is still not operational for use in the creation of global comparable data. There remains some work with regards to defining exactly what an “incident” is and the potential number of global incidents that need to be collected will be a great challenge. There will also be difficulty finding reliable information on such a measure globally. To illustrate the potential scope of such a project, it can be noted that according to statistics from Iraq there were on average 175 attacks per day by insurgents and militias in December 2006 [7]. Simply counting the number of incidents may limit our understanding of and actually misrepresent the severity of a phenomenon. It is necessary to remain focused on the scale of different incidents, as the impact of the attacks on the World Trade Center in New York on 11 September 2001 has been significantly larger than another terrorist incident that occurred just over a month later near Susanville in California. The attack on the twin towers led to 2,749 deaths, while the attack by the Earth Liberation Front resulted in a government owned barn being set on fire. 1.2. Injuries as a Measure of the Severity of Conflict The immediate effect of disrupting economic and social life and spreading fear can be even greater if some casualties occur in these attacks. According to the original military definition, the term “casualty” referred to all who were lost to active military service, meaning that not only the dead but also those severely wounded, captured, deserted and missing were taken into account. Indeed, it is not an uncommon view among warring parties that wounding an opposition soldier is better than killing the soldier, as the immediate effect is that other opposition soldiers will stop fighting to take care of their colleague. Injured and wounded victims in a conflict will also require resources through hospital treatment and help with reintegrating into society. Conflicts that lead to many injuries will also have long-term impacts as the affected society will have to continue to accommodate victims even after the fighting has ended. It would therefore make sense to measure the severity of conflicts by counting the number of injuries resulting from the fighting. Such an approach would however have to deal with similar challenges faced by attempts to measure severity through the number of incidents. It would be necessary to provide a more detailed definition of “injury” and it will be very difficult to collect global information about all injuries.

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J. Kreutz / Calling a Conflict a Conflict: Violence and Other Aspects of War

1.3. Refugees as a Measure of the Severity of Conflict A third potential effect of war that has a great impact on societies are the numbers of refugees created by conflicts. This aspect could also be employed as a means of measuring severity both immediately and over time. Immediate effects are that refugees in the vicinity of conflict locations will need resources in the form of food, health care, and shelter. At the same time the country will be less able to produce these resources as the refugees have left their jobs, houses and lives to avoid the conflict. Furthermore, after the conflict has ended, many refugees will not return as they are worried about the security situation in their old home and may have created a new life somewhere else. The result will be that when a society needs to be rebuilt after a conflict, the most able members may not be able or willing to participate. Even though the creation of refugees sometimes can indicate the severity of conflict and there is accessible global information available to prove this point, it is a measure with limited use. Forced migration is not consistent across all conflicts, instead it depends on several other factors such as the location of the fighting and the type of violence employed. Interestingly, the number of fatalities in the conflict is not linked with increased number of refugees [8]. Refugee flows are not only caused by conflict, but also for a number of other reasons such as the risk of human rights abuses, lack of democracy, and environmental disasters. These different reasons for why people flee their home countries can be difficult to separate. According to figures from UNHCR, there were over 340,000 refugees from Vietnam in the world on 1 January 2005, despite the country not being involved in a conflict since 1988. Rather than using forced migration as an indicator of the severity of conflict, it is a phenomenon that needs to be studied on its own in order to provide more information about the relationship between refugees and war.

2. Non-violent Deaths in Conflict The basic definition of war for most conflict data projects generally consists of the following three criteria: identifiable organized actors, identifiable political objectives, and a given threshold of deaths caused by the fighting between these actors. One of the most disputed aspects of the definition is with regards to the focus on deaths caused by fighting. It has been suggested that it would be better if the data provided information about war-related deaths, including the so-called indirect deaths caused by, for example, disease and malnutrition. 2.1. Direct and Indirect Deaths Following epidemiological surveys in the eastern part of the Democratic Republic of Congo, the International Rescue Committee (IRC) reported that the conflict had led to some 3,8 million deaths, the large majority were due to treatable and preventable diseases [9]. This estimate was significantly higher than those provided by conflict data projects, mainly because it included both direct and indirect war deaths. The former are fatalities that are directly caused by violence, while the latter are caused by “such phenomena as illness, disease, or starvation that would not have occurred in the absence of conflict” [10]. The suggestion that indirect conflict deaths should be

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included in severity estimates on conflict is often expressed by case study experts who argue that not including all aspects of a given conflict is morally wrong as the suffering of the population in a particular conflict location should not be ignored. In a study about the consequences of a conflict in a particular country such an approach is clearly advantageous, but it produces limitations for systematic studies trying to identify structural factors that contribute to human suffering. It is worth bearing in mind the lessons of Kalyvas (2006) and Durkheim, who noted that social scientists cannot be accused of wishing to condone crime or be devoid of all moral sense just because they study a phenomenon through a “cold, dry, analysis” [11]. Indirect deaths from starvation, disease, and the like are significant problems that often do not receive enough attention by the policy community. However, the solution is not to incorporate these figures into the conflict severity estimates. Any such attempt would only make our understanding of conflict less precise, it would be harder to identify the end of conflicts, and there is a risk that the indirect deaths by malnutrition or disease would receive even less attention than they currently do. Taking the example of the Democratic Republic of Congo, the argument that the severity of the conflict is better represented by the mortality figure of 3.8 million victims would suggest a similar approach to other countries in the region. Thus, the short-lived conflict in the neighbouring Republic of Congo 2002 where around 100 people were reportedly killed should be reported as an estimated 45,000 casualties [12]. Furthermore, the violence between the government and rebel groups in the Democratic Republic of Congo ceased in late 2001 and a peace agreement in December 2002 solved the political aspects of the conflict. Even though the conflict behaviour had ended, the IRC surveys included the mortality rate in the post-conflict phase. In order for us to be able to analyze the phenomenon of conflict, there is a need to identify when the conflict has ended even though the long-term effects of the conflict often remain. According to Ghobarah et al [13], many victims of indirect deaths may occur after the fighting has ended. They find that “civil wars greatly raise the subsequent risk of death and disability from many infectious diseases”, and also there is a risk in post-conflict societies for “increases in homicide, transportation accidents, other injuries, and cervical cancer” [13]. Finally, problems concerning malnutrition and disease are not only caused by conflicts, but are common among refugee populations and many poor countries. The occurrence of a conflict in the same location may worsen the situation as it may be more difficult to administer humanitarian assistance. In the end, without more studies clarifying the links between the direct and indirect deaths in conflict regions it will continue to be difficult to design policies in response to future situations. 2.2. Deaths of Combatants Outside of Combat One of the most commonly reported type of fatality statistics from conflicts consist of so-called combatant deaths. Information about the number of combatants killed has long been used by military strategists in analyzing the capabilities, tactics, or for comparing militaries’ cultural or organisational sophistication [14]. In the end, however, the forces of the conflict actors consist of individuals who during conflict often become exposed to extreme situations. On 3 June 2006, a Chinese military airplane crashed in the province of Anhui, some 200 km west of Shanghai, which led to 40 people being killed. It was just one of several reported incidents of deaths during military training in China that year. There have not been any suggestions that the victims of the accident should be considered as conflict-related and there is no conflict

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in China registered by the most recent updated UCDP dataset [15]. However, if the incident had occurred in Iraq and involved an Iraqi government airplane, a dataset focusing on combatant deaths would have included the victims of the accident as part of conflict severity. Similar to the arguments for why injuries could be a useful measure of the severity of a conflict, the casualties in the form of accidents and suicides among military personnel can be politically important. Although, these types of incidents are less useful for explaining the amount of fighting in a conflict. Additionally, relying solely on combatant deaths will create difficulties in regard to the comparability of conflict and non-conflict locations and for identifying the start and end-dates of conflicts.

3. The Difference between Violence and Conflict A common mistake is to assume that all violence that takes place in a country where a conflict is active must be part of that situation. Such a statement is common even though the logic behind it is rarely investigated since it would suggest that either (a) there is no violence in countries without conflict, or (b) that all other types of violence ceases when a war starts in a country. This can be disputed, as arguably the opportunities for criminal violent behaviour increases rather than end during a conflict. It is possible, with the help of a careful examination of the definitions used for identifying armed conflict, to distinguish between conflict violence and other types of violence. In particular, the following aspects of violence need to be assessed: 1. Who is the perpetrator of the violent act? 2. Who is the target of the violent act? 3. Why is the perpetrator employing violence against the target? A basic overview of the first two aspects can be seen in Table 1, while the third aspect is qualitative and needs more deliberation. The methods used for collecting information concerning these factors differ in different data projects and have evolved over time. Sometimes, projects provide an estimate for the yearly activity of conflicts based on an evaluation of the existing material, while other projects claim to have detailed information for each incident. It can be argued that focusing on each incident and then aggregating the information into a yearly conflict estimate provides a higher level of validity with regards to the aspect that is coded. There is, however, a risk of less reliability as the number of “unclear” incidents increases. One potential approach to handling such problems is the use of several estimates (for example the UCDP uses a low/best/high yearly estimate system) and then in the presentation to continue to focus mainly on the “best” estimate given. For the conflict in Iraq, for example, UCDP estimate 2,802 to 6,622 deaths in incidents when both the perpetrators and the victims could be identified as part of the conflict. There were, however, numerous other incidents where the attack clearly was targeting the Iraqi government forces, but also where there was no evidence or statement about whether the perpetrators of the attack were an organized group. Such incidents, which nevertheless were deemed to be likely to be battle-related, led to an additional 2,758 to 2,894 deaths. These figures do not include any attacks on civilians, fighting between different organized groups or the numerous victims that were found killed for unclear reasons throughout the year.

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Table 1. Perpetrators and victims of violence in conflict countries Who (perpetrator) State

Organized group

Individual

Who (target) State/soldier

interstate?

Intrastate?

crime

Organized group

Intrastate?

non-state

crime

Non-combatant

one-sided?

one-sided?

crime

3.1. The Perpetrators of Violence One of the key factors for the pioneers in the systematic study of war was to explain the fighting between different states. The consideration of military capabilities or domestic opinion are but two examples of the many studies carried out in this area. Following the development of comprehensive conflict data projects, it soon became clear that intrastate conflicts–or civil wars–were at least as common as fighting between states. According to the UCDP, the use of force by groups seeking to secede from a country or in the contest for political power has been more predominant every year since 1946 than warfare between states. The terminology in table 1 was chosen from the different types of data collected on organized violence that was carried out by the UCDP and presented annually in the Journal of Peace Research and the Human Security Report. States are the traditional key members of the international system and their use of violence can manifest itself in both inter and intra-state conflict. In intra-state conflicts, the representatives of the state will be the target of attacks from organized groups, but such groups often also use violence against each other. There is, however, an additional dimension that often has been overlooked in discussions about armed conflict and strangely has also been neglected by most conventional criminologists, namely individuals’ increased use of violence during, but not exclusively within, wartime. One of the first projects focusing on the systematic study of war theorized that the phenomenon occurred as a consequence of the breakdown of social and cultural relationships [16]. During the circumstances of war, it was argued by contemporary scholars, all the factors that lead to crime are driven upwards: “family life is ripped apart, children are neglected, destitution spreads, while scarcity of goods generates theft and begets illicit markets. Crime is also caused by a general demoralization, and violent behaviour increases as a mimetic outcome of the spectacle of ‘killing, maiming and terrible destruction’. [...] The dark figure of crime is assumed to go up, due to the weakening of institutional agencies such as the police and the judiciary” [17]. Individuals can sometimes attack and kill representatives of the government, such as police and members of organized groups. Indeed, individuals may even participate in large-scale violent demonstrations that force the government out of office without it being a case of armed conflict. Following a sudden fuel price hike in Yemen 2005, anti-government demonstrations turned violent as some individuals in the protest fired on police. The demonstrators were not part of an organized group but ended up in gun battles with local shop-owners who had armed themselves to prevent looting.

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The example from Yemen illustrates another effect where instability, or the outbreak of armed conflict, can make neighbourhoods, families, or friends choose to arm themselves as self-defence forces or potential vigilante mobs. Such developments are often more difficult to overcome than trying to settle the conflict as the concept may become part of the official or unofficial business community and the groups are less likely to demobilize voluntarily. One of the countries in the world where such structures are most visible is Colombia, where at times some 80 per cent of the casualties of violence are not caused by fighting in the conflict [18]. Indeed, the government has recently been forced to negotiate a demobilization agreement including some political concessions with the paramilitary groups who originated as private armies protecting large landowners and drug lords. These types of arrangements are not only found in conflict countries as, according to Guatemalan human rights organizations, vigilante death squads attacked and killed 57 suspected criminals in February 2006 alone because of the alleged poor performance of the local police. 3.2. The Targets of Violence The second important information necessary to classify a situation as a conflict is to focus on the victims, or rather the targets, of the violence. Most conflict datasets focus primarily on victims of the fighting, which includes either the combatants from the fighting parties or also the so-called collateral, or civilians caught up in the violence. There is an important distinction between these two approaches as the legal guidelines for warfare, for example the Fourth Geneva Convention, makes a distinction between combatants and legitimate military targets on one side and civilian and civilian objects on the other side. Despite the advent of so-called “smart bombs”, it is still very common that civilians are hurt in modern warfare, especially in urban areas such as the conflict in Iraq. However, it would be illogical to count only the combatant deaths in a battle where some civilians are caught in the crossfire, hence the use of battle-related deaths as a useful indicator for conflict severity. This measure consists of all people, soldiers as well as civilians, who are killed in military operations during a war and is useful to describe the scale, scope and nature of the fighting that has taken place. Thus, providing that the other criteria for what constitutes an armed conflict are fulfilled, all people killed in warfare are registered and aggregated to identify the severity of conflicts. For 2006, there were 15,994 (low estimate) to 30,865 (high estimate) people killed in conflicts according to UCDP, a figure which represented a global increase of some 37 per cent1 compared to the year before. In the Human Security Report 2005 [19], it was suggested that the traditional focus on conflicts between states, or between states and rebels, was incapable of providing the full extent of global battle deaths. It introduced an additional dataset of fighting between organized groups, with or without political motivations, called the non-state conflict data. There is so far only systematic data on non-state conflicts since 2002, but the phenomenon has been found in countries where the government is challenged and elsewhere. One common factor that seems to lead to the outbreak of non-state conflict is that different rebel groups are not only fighting against the government, but also among themselves. However, there are also cases observed when the government encourages such behaviour. After the rebellious Communist Party of Burma in 1989 was dissolved as several of its military units mutinied due to dissatisfaction with the 1 This increase is calculated using the “best” estimates.

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leadership, the strongest military force that emerged was the United Wa State Army (UWSA). The new group wanted to secure the political rights of the ethnic Wa group in north-eastern Burma. Government representatives quickly opened up talks with the UWSA leaders and offered a ceasefire with some local autonomy for the Wa providing the group used its military strength against rebels in its vicinity. UWSA agreed in principle to the agreement, but soon declared it was not willing to fight its former allies in the Kachin Independence Organization. It did not have such qualms about other antigovernment groups in the area and has ever since been involved in battles against forces such as the Mong Tai Army and the Shan State Army-south Command. Fighting between organized groups influences societies and can, as the example illustrates, also influence the dynamics of civil wars. It deserves to be treated as a separate unit of analysis that sometimes, but not always, can influence conflicts. Based on the limited knowledge we currently have of this phenomenon, it appears that non-state conflicts are more common in countries that recently have ended a civil war. This in turn may lead to several potential findings concerning, for example, the quality of governance and the availability of arms in such countries. The battle, whatever form it may take, should be understood as a phenomenon that consists of two combatant sides with potential civilian side-effects. This is a distinctively different concept than what UCDP refers to as one-sided violence, even though this phenomenon sometimes has been used during conflicts or even as a strategy against the opposition. One-sided violence is defined as events when an organized group, either the government of a state or any other organized entity, deliberately targets and kills civilians. The definition incorporates some incidents that elsewhere can be defined as genocide, politicide, terrorism, mass murder, ethnic cleansing, or massacres, but at the same time clearly delineates a certain empirically distinctive type of behaviour. Some commentators have argued that events such as the deaths caused by the Pol Pot government in Cambodia in the 1970s, or by the Rwandan government and its’ affiliated militias in 1994 should be included as part of the severity of these conflicts [3]. Such an approach would not necessarily improve the information provided about these conflicts, or outbursts of severe one-sided violence, without a closer investigation of the events. After the Khmer Rouge managed to take control over “Democratic Kampuchea” in 1975, there followed two years of peace from the civil war. The government ended up fighting interstate conflicts against Thailand and Vietnam during this time and there were some reports of local commanders in the southern and eastern districts of the country that mutinied against the government. Unfortunately it has been difficult to access reliable information about these events and it nevertheless did not constitute a large-scale war. The violence unleashed by the Pol Pot government during these years may have been fuelled by suspicion about potential rebellions, although there has not been any evidence presented to support the claim that the main reason for the forced evacuation of the cities and the mass executions was the conflict. In Rwanda, the conflict was in a process of de-escalating following the establishment of a multiparty government in 1992 and the Arusha peace accords in 1993. How this decrease of conflict intensity could have influenced the Hutu extremists into overthrowing the government in April 1994 and initiating genocide is a question that needs to be further studied. Nevertheless, it is a matter that should not be confused with the conflict itself.

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3.3. Why the Perpetrators Attack the Target Violence can take many forms, and only when registered in the form of fighting between organized entities, of which at least one is the government of a state, can it be considered a conflict. There is, however, another important aspect of violence that needs to be discussed. Violence, even between the types of parties that have been described in this chapter, does not necessarily constitute a conflict. At the same time, a conflict must not necessarily be violent. According to Wallensteen [20], a conflict is defined as a social situation where at least two parties strive to acquire, at the same time, the same limited resources. According to this basic definition, these “parties” could be individuals, organizations, or states and the resources that are competed for could be almost anything. As a consequence, it can thus be argued that there exist numerous active conflicts in any given country and at any given time. It is when these conflicts are concerned with the core aspects of state sovereignty, or “who is to make authoritative decisions over a number of people in a certain area” [21], and the actors choose to employ violent acts against each other that it constitutes an armed conflict. Indeed, some conflict data projects do not include the notion of violence at all in their definition of conflict, such as the project at the University of Heidelberg. Others focus on conflicts that include violence or the threat of violence, which is the case for the MID and the ICB projects. As was the case in the discussion on battle-related deaths when it is the intent of the perpetrator that classifies a situation as part of an armed conflict, it is the intent of the state(s) and/or the organized group that creates the conflict. Measuring intent is extremely difficult and has to be empirically based, either through analysing the actions (if rebel group X fires on government soldiers, it can be assumed that their target is the soldiers) or by basing the coding on statements made by the actors. Since the criteria for identifying a conflict consists of having good information about both the actions and the statements, there will always be a degree of uncertainty surrounding some cases. Hence, UCDP maintains an updated list of unclear cases which, when more information becomes available, may eventually become listed as active conflicts. One example of this is the conflict in Pakistan (Baluchistan) which in 2005 was reported as unclear, but in the 2006 update of the dataset has been included as active in every year from 2004 to 2006. To also include the political aspect, the incompatible statements made by states or organized groups into an overview would remove some of the uncertainty with regard to which situations constitute armed conflicts (see Table 2).

Table 2. Classification of violent acts with or without political incompatibilities Perpetrator and Target State targeting other state State targeting org. group State targeting civilians Org. group targeting State Org. group targeting other org. group Org. group targeting civilians Individual targeting state Individual targeting org. group Individual targeting other individuals

With political incompatibilities? Yes No interstate conflict ? intrastate conflict ? one-sided one-sided intrastate conflict ? non-state non-state one-sided one-sided crime crime crime crime crime crime

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In the analysis of armed conflict, it is of great importance to retain the understanding of the political nature of the phenomenon. There is an important factor that separates armed conflict from other phenomenon which is apparent in Clausewitz’s acknowledgement that violence is a means to reach a political end. UCDP have chosen to focus on statements by the actors in a conflict that spells out their incompatible positions over a political issue concerning government or territory. These situations are different compared to occasional outbursts of violence between states, as there are other means available for reaching the political objectives such as negotiations or sanctions. Soldiers from neighbouring countries that kill each other may not necessarily constitute an armed conflict, if there is no stated incompatibility. For example, soldiers from Thailand and Myanmar fired at each other for about 30 minutes in August 2006 after a misunderstanding about the exact location of the border. There were no casualties in this incident, but there has been in similar situations in previous years. Similar incidents can occur between government representatives, such as police and members of organized groups, even though they have not stated any political objectives against the administration of the state. Almost war-like fighting has taken place with organized criminal groups who sometimes have launched large-scale campaigns against government targets, such as the Colombian group “Los Extraditables”, led by Pablo Escobar, in the early 1990s. In 2006, fighting between the Brazilian police and the group PCC (Primer Comando de la Capital) led to over 100 casualties, which was more than many observed armed conflicts. The PCC did not, however, have any proclaimed political ambitions apart from their criticism of the conditions in Brazilian prisons. Without clear political goals, it is not possible to identify potential compromises or solutions that can stop the violence even though it obviously had a great impact on the life of citizens in Sao Paolo. To develop systematic definitions and start collecting information on these types of incidents is an important future development for the study of organized violence, but not necessarily for scholars focusing on the phenomenon of war.

4. Conclusion Armed conflict, or war, is a phenomenon of the greatest severity, and the effects for a society experiencing it can hardly be underestimated and may be felt for decades after the actual fighting ended. In order to improve our understanding about what causes war, what makes it more deadly, what can be done to limit it, or how it can be stopped, the research community faces substantial challenges. Using advanced statistical methods, it is possible to identify structural factors such as poverty or the management of income from national resources and this knowledge can help policy makers design long-term plans to limit the risk of having to deal with the outbreak of conflict. These studies must, however, be accompanied with a detailed investigation of wars to make it possible for us to act quickly, using the correct information and the right response, and improve our ability to stop the violence before it has spread across a country. In order to meet these two challenges, it is of utmost importance that the research as well as policy community have access to reliable and comparable information from countries around the world – in conflict as well as in peace. The best information only becomes available through the combination of different methodologies, as mortality studies inform us of the amount of destruction in a war-torn country while media based data can tell us more details about who, how, and when the deaths occur.

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In order to improve the usefulness of, and to promote the collection of data on organized violence, whether it be political or spontaneous, it is important to use clear and transparent definitions. A multitude of different data collection projects is not a problem, as there are numerous important factors of violent and non-violent phenomenon that may occur in a conflict country that currently is not systematically collected. Some of the examples mentioned in this chapter are the indirect deaths of conflict or the criminal statistics for conflict countries, which are not yet available on a global scale. Some projects coming out of the COW data effort such as the MID datasets have pioneered studies of the micro-foundations of conflict, and recent additions of the UCDP such as the one-sided and non-state conflict datasets have followed suit. Much remains to be done and the ever present challenge for data collection efforts is not the lack of ideas, but the hunt for additional funding. As policy makers around the world increasingly emphasize the need for evidence based policies, it must be acknowledged that there is a value in keeping existing data projects updated and revised. These are the building blocks for scientific progress and it is only with detailed information for long term series that the research community will be able to advance our knowledge of armed conflict. Finally, it is of great importance that researchers as well as data users within the policy community and journalists refrain from simplifying the complexity of conflict. Datasets could, and should, always be scrutinized in order to identify problematic areas and the need for improvement, but they should not be criticized for adhering to its definitions. One of the most policy-relevant research projects during the last decade has been conducted by Barbara Harff with the ambition of designing a model to assess risks of future genocides and politicides. One of her findings is that the risk of genocide/politicide increases when there is an intrastate conflict [22]. However, Harff would never have been able to even test that argument unless she had access to systematic data which treated conflict as something different from the attacks on civilians that constitute genocide/politicide. The importance of more disaggregated data for different phenomena, even if they occur at the same time in the same country, could not be clearer, especially if Professor Harff’s recommendations succeed in preventing genocide somewhere else. One of the important future developments for conflict data collection and research projects is to improve our understanding about different aspects of organized violence and how these interact. The increased use of the term human security is aimed at promoting research focusing on the threats against individuals, and the best approach to fulfilling that ambition is to investigate the diversity of threats rather than referring to them all as a single phenomenon.

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Singer, J. David. 1972. “The Correlates of War Project: Interim Report and Rationale.” World Politics 24: 243-70. Kaldor, Mary. 2002. New and Old Wars: Organized Violence in a Global Era. Cambridge: Polity Press. Leitenberg, Milton. 2006. “Deaths in Wars and Conflicts in the 20th Century, 3rd Ed.” Cornell University Peace Studies Program Occasional Paper No 29. Melander, Erik, Magnus Öberg and Jonathan Hall. 2006.”The New Wars Debate Revisited: An Empirical Evaluation of the Atrociousness of New Wars.” Uppsala Peace Research Papers No 9. Uppsala: Dept. of Peace and Conflict Research. Kirk, Robin. 2003. More Terrible than Death: Massacres, Drugs and America’s War in Colombia. New York: Public Affairs. Goodin, Robert E. 2006. What’s wrong with terrorism? Cambridge: Polity Press.

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O’Hanlon, Michael E. and Jason H. Campbell. 2007. Iraq Index: July 5, 2007. (www.brook.edu/fp/ saban/iraq/index.pdf). Accessed 9 July 2007. Melander, Erik and Magnus Öberg. 2007. “The Threat of Violence and Forced Migration: Geographical Scope Trumps Intensity of Fighting.” Civil Wars 9(2): 156-173. Coghlan, Benjamin; Richard J Brennan, Pascal Ngoy, David Dofara, Brad Otto, Mark Clements, and Tony Stewart. 2006. “Mortality in the Democratic Republic of Congo: A Nationwide Survey.” The Lancet 367: 44-51 Wille, Christina and Keith Krause. 2005. “Behind the numbers: Small Arms and Conflict Deaths.” Small Arms Survey 2005. Geneva: Small Arms Survey. Kalyvas, Stahis N. 2006. The Logic of Violence in Civil War. New York: Cambridge University Press. Mathers CD, Bernard C, Iburg K, Inoue M, Ma Fat D, Shibuya K, Stein C, Tomijima, N 2003. “The Global Burden of Disease in 2002: data sources, methods and results.” GPE Discussion Paper No. 54. (www.who.int/evidence). Accessed 9 July 2007. Ghobarah, Hazem; Paul Huth, and Bruce Russett. 2003. “Civil Wars Kill and Maim People: Long After the Shooting Stops.” American Political Science Review 97(2): 189-202. Lacina, Bethany and Nils Petter Gleditsch. 2005. “Monitoring Trends in Global Combat: A New Dataset of Battle Deaths.” European Journal of Population 21(2–3): 145–165. Harbom, Lotta and Peter Wallensteen. 2007. “Armed Conflict, 1989-2006.” Journal of Peace Research 44(5): 621-632. Sorokin, Pitirim A. 1937. Social and Cultural Dynamics, 4 vols. New York: American Book. Bonger, Willem Adriaan. (1936) An introduction to criminology; translated from Dutch by van Loo, Emil. London: Methuen. cited by Ruggiero, Vincenzo. 2005. “Criminalizing War: Criminology as Ceasefire.” Social and Legal Studies 14(2): 239-257. Bejarano, Jesús Antonio. 2003. “Violence, Security and Economic Growth in Colombia, 1985-1995.” Colombian Economic Journal 1(1). Mack, Andrew, Ed. 2005. Human Security Report 2005: War and Peace in the 21st Century. New York: Oxford University Press. Wallensteen, Peter. 1994. Från krig till fred (From War to Peace.) Stockholm: Almqvist & Wiksell. Heldt, Birger. 1993. “Armed Conflicts over Government and Territory 1989-91”, in Heldt, Birger, Ed. States in Armed Conflict 1990-91, 2nd Ed. Uppsala: Department of Peace and Conflict Research Report No. 35. Harff, Barbara. 2003. “No Lessons Learned from the Holocaust? Assessing Risks of Genocide and Political Mass Murder since 1955.” American Political Science Review 97(1): 57-73.

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