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Peace Research Institute Oslo
SVACSexual Violence in Armed
Conflict
Data collection, challenges and preliminary findings
Oslo, November 2010
Ragnhild Nordås, PRIO and Notre DameDara K. Cohen, University of Minnesota
Outline
• About the project•Motivation• Data collection• Preliminary results• Lessons and future work
2
SVAC - Motivation and backdrop
• “Rape is one of the greatest peace and security challenges
of our time.” UN secretary-general's special representative on
sexual violence in conflict, Margot Wallstrom
• Current data are mostly case studies, focused on the same cases of the worst sexual violence (Bosnia and Rwanda)– A better research design would analyze a universe of all
cases, including where sexual violence occurred and where it did not
To devise an effective prevention strategy, more systematic knowledge is needed
3
Project goal
• Forecasting for prevention• Data needs – A comprehensive dataset on sexual violence in armed conflict
1989-2009 by all major actor types (state and non-state)• First step: Pilot project on conflicts in Africa, 2000-2009
– Pilot project funding: Grant from the Norwegian Ministry of Foreign Affairs (Sept-Dec 2010)
• Second step: Additional years and geographic regions– Research suggests that the problem is worldwide, not
only Africa (Cohen 2010)– Pending additional funding
• Long-term goal– To guide policymakers towards more effective measures
against sexual violence in armed conflict and post-conflict situations
4
SVAC project staff
• Head researchers
Inger Skjelsbæk Dara Kay Cohen Ragnhild Nordås Scott Gates Håvard Strand
(Minnesota)
• Consultative group
Elisabeth Wood (Yale) Mia Bloom (Penn State) Chris Butler (New Mexico) Amelia Green (Yale)
5
UCDP/PRIO Armed Conflict Dataset v4-2009
1
2
3
Pilot: Region 1, conflicts active in 2000-2009
6
SVAC data: What is sexual violence and ”armed conflict?”
• SVAC will use the International Criminal Court (ICC) definition: – includes rape, sexual mutilation, sexual slavery, enforced
prostitution, forced pregnancy, and enforced sterilization – importantly, definition does not exclude the existence of female
perpetrators and male victims of sexual violence • SVAC uses the UCDP definition (dataset) on Armed Conflict: – Defines conflict as “a contested incompatibility that concerns
government and/or territory where the use of armed force between two parties, of which at least one is the government of a state, results in at least 25 battle-related deaths”• ”war” = 1000 battle-related deaths in a calendar year
– Types of conflict: (1) Intrastate armed conflict(2) Internationalized internal armed conflict (3) Interstate conflicts
7
SVAC dataset: Unit of analysis
• Conflict-actor-year– A given conflict actor (state/militia group,
rebel group)– In a given conflict – In a given year• Example: the sexual violence perpetrated
by the RUF in Sierra Leone in 1995
8
SVAC dataset: Dimensions
• Perpetrators: Who commited the violence? (Armed group, ethnicity, gender)
• Victims: Who were the victims? (Gender, race, ethnicity, age)
• Magnitude: How intense was the violence? (Isolated incidents, widespread)
• Location: Where did the violence happen? (Part of the country, location)
• Timing: When did the violence happen? (Early in the war, during peace talks)
• Form: What types of sexual violence? (rape, gang rape, forced marriage)
9
Main data sources in pilot
• Five major data sources
1. US State Department Human Rights reports (annual)
2. Amnesty International 3. Human Rights Watch 4. International Crisis Group5. DCAF, Sexual Violence in Armed Conflict
10
Documentation and Reliability
• Conflict manuscripts – Background information in document with
searchable headings
• Coding decisions are double-checked for consistency– detect any misunderstandings and/or systematic
biases– calculate intercoder reliability scores
11
Pilot sample
• 28 armed conflicts total that are active in Africa in 2000-2009
• These involve 120 conflict actors • Initial phase of pilot are 8 high priority conflicts
RA #1 RA #2 RA #3 RA #4Sudan Sierra Leone Rwanda DRC
Eritrea Cote d’Ivoire Burundi Angola
Ethiopia Guinea Nigeria Uganda
Somalia Mali Central African Rep. Congo
Algeria Liberia Chad
Senegal
Guinea Bissau
12
Preliminary findings from first 8 countries
• There is variation in perpetration of sexual violence both across and within these conflicts
• Magnitude by actor group type– Most state actors are perpetrators– 25% of pro-government militias are perpetrators– Less than 50% of rebel groups are perpetrators
• Variation over time– Both state and non-state perpetrators refrained from
sexual violence in at least some years– Policy implication: Sexual violence is not a constant,
inevitable consequence of wartime
13
Preliminary findings: Post-conflict violence
• Data show sexual violence by armed groups continues after conflict– 25% of conflict actors engaged in some sexual violence post-
conflict
• Only focusing on the period of conflict misses the full scale of conflict-related sexual violence– Implications for policy: Peacekeeper presence should
continue even after deaths have stopped; peace processes should focus also on ceasing non-lethal violence
• Suggests that lethal violence is not perfectly correlated with sexual violence– Implications for research: Need to collect separate data and
to develop separate theories on sexual violence
14
Lessons: Measuring SV--Challenges/opportunities
• Policy memo on challenges and opportunities for cross-national data collection on SVAC (February 2011)• What are the challenges?• Biases in sources
– What is sexual violence? – Measuring magnitude• Under-reporting • Over-reporting• What counts?
– Beyond magnitude• Who are the perpetrators/victims• Locations of violations• Timing
15
Data/methods recommendations
• Importance of a clear, standard definition• Establishing a baseline measure from pre-
conflict• Data on both perpetrators/victims• Time-variant data• Location data• Data triangulation – verification from several
sources–More comprehensive search on selected
cases– Comprehensive and narrow search to be
compared for content
Peace Research Institute Oslo
Thank you
Conclusions
•Will be most comprehensive data collection• Funding• Policy briefs (2011)