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Peace Research Institute Oslo SVAC S exual V iolence in A rmed C onflict Data collection, challenges and preliminary findings Oslo, November 2010 Ragnhild.

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Presentation on theme: "Peace Research Institute Oslo SVAC S exual V iolence in A rmed C onflict Data collection, challenges and preliminary findings Oslo, November 2010 Ragnhild."— Presentation transcript:

1 Peace Research Institute Oslo SVAC S exual V iolence in A rmed C onflict Data collection, challenges and preliminary findings Oslo, November 2010 Ragnhild Nordås, PRIO and Notre Dame Dara 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 2

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 3

4 SVAC project staff 4 Head researchers Inger Skjelsbæk Dara Kay Cohen Ragnhild NordåsScott 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 5 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 6

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 7

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) 8

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 Group 5.DCAF, Sexual Violence in Armed Conflict 9

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 10

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 11 RA #1RA #2RA #3RA #4 SudanSierra LeoneRwandaDRC EritreaCote d’IvoireBurundiAngola EthiopiaGuineaNigeriaUganda SomaliaMaliCentral African Rep.Congo AlgeriaLiberiaChad 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 12

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 13

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 14

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 15

16 Peace Research Institute Oslo Thank you Conclusions Will be most comprehensive data collection Funding Policy briefs (2011)

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