https://www.stephenoconnell.org/tags/displacement/Recent content in Displacement on Stephen D. O'ConnellHugoenThu, 02 Jul 2026 18:01:10 -0400https://www.stephenoconnell.org/project/ml-sampling-frames/Fri, 01 May 2026 00:00:00 +0000https://www.stephenoconnell.org/project/ml-sampling-frames/<p>Survey research on conflict and displacement depends on the reliability of sampling frames. We show that common approaches to developing these frames may underrepresent populations central to this research: displaced people, returnees, and civilians exposed to violence. We develop a hybrid approach to sampling frame generation that combines machine-learning (ML)-generated building footprints with satellite imagery. We test the approach in displacement-affected Iraqi communities. Our approach achieved 87% residential accuracy overall, and our data reveal non-random omissions in the common ML-only approach. We find systematic coverage differences across frame-generation methods. Manual methods capture more rural internally displaced persons and urban returnees, due to informal shelters and wartime reconstruction. Our hybrid ML-and-satellite sampling can mitigate coverage error and improve inference about conflict and displacement.</p>