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Session Submission Type: Created Panel
This panel brings together papers that address problems of bias in data or interpretation. Bias may stem from the positionality of the researcher, from the identity or motivations of informants, from missing or poor quality data, or from the particularity of the case under examination (thereby limiting generalizability).
Causal Identification When Nothing Is Certain: Working with the UN in Darfur - Sara Abdus Salam Ansari, Brown University; Paul Thissen, International Initiative for Impact Evaluation (3ie)
Improving External Validity of Lessons Learned from Case Studies in Evaluation - Derek Beach, University of Aarhus
Methodological Issues in Studying North Korea - Jinah Kwon, University of Sheffield
Vulnerability to Experiences of Sexual Harassment and Assault during Fieldwork - Stacey Leigh Hunt, Auburn University; PĂ«llumb Kelmendi, Auburn University; Isaac Pollert, Penn State University; Alexandra Filindra, University of Illinois at Chicago
The Fundamental Problem of Interpretive Inference - Richard Nielsen, MIT; Jasmine Hope English, Stanford University