Shades of truth and lies: Interpreting testimonies of war and violence

Lee Ann Fujii ()
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Lee Ann Fujii: Department of Political Science, George Washington University

Journal of Peace Research, 2010, vol. 47, issue 2, 231-241

Abstract: How should researchers treat questions of veracity when conducting interviews in settings rent by large-scale violence, such as war and genocide? To what extent should researchers trust narratives that are generated in politically sensitive contexts? The article argues that the value of narrative data does not lie solely in their truthfulness or accuracy; it also lies in the meta-data that accompany these testimonies. Meta-data are informants' spoken and unspoken thoughts and feelings which they do not always articulate in their stories or interview responses, but which emerge in other ways. This article identifies and analyzes five types of meta-data: rumors, inventions, denials, evasions, and silences. The article argues that meta-data are not extraneous to our datasets, they are data and should be viewed as integral to the processes of data collection and analysis. Meta-data indicate how conditions in the present shape what people are willing to say about violence in the past, what they have reason to embellish or minimize, and what they prefer to keep to themselves. Attending to meta-data is important for responding to informants' fears about talking to a researcher and to ensure informants' safety after the researcher leaves the field. It is also crucial for the robustness of researchers' theories and knowledge about political violence and other political phenomena. The article draws from the author's nine months of fieldwork in Rwanda in 2004, as well as the literature on conflict and violence from political science, anthropology, history, and sociology.

Keywords: fieldwork; genocide; narrative data; post-conflict; rumors; silences; war (search for similar items in EconPapers)
Date: 2010
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Persistent link: https://EconPapers.repec.org/RePEc:sae:joupea:v:47:y:2010:i:2:p:231-241

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