UC Berkeley

In this dissertation, I examine two human right estimation problems.

First, I assess data on child abductions from El Salvador's civil war. Between 1979 and 1992, El Salvador was wracked by conflict between leftist guerrilla groups and right-wing nationalist governments. One feature of the conflict was the abduction of children by government military forces, or the forced surrender of children to those same forces. Since 1994, La Asociación Pro-Búsqueda de Niñas y Niños Desaparecidos has investigated cases of these child abductions. To date, they have opened more than 950 cases and located nearly 400 abducted children (now, young adults). The organization remains active, and new cases come to light each year. In Chapter 2, I examine Pro Busqueda's data, assessing what can be said to date about the total as yet unknown number of abductions that occurred. I demonstrate that more abductions occurred than the number of currently known cases discuss capture-recapture estimates under a range of assumptions about the data available today. I then lay out a plan for updating estimates as new data becomes available.

Then, I examine current data on deaths from the ongoing conflict in Syria. Early in the conflict, the United Nations Office of the High Commissioner for Refugees (UNOHCR) contracted with statisticians at the Human Rights Data Analysis Group (HRDAG) to analyze data from multiple human rights groups that were documenting deaths from the conflict there. HRDAG produced three reports from the United Nations and has maintained ongoing relationships with the local human rights groups that are collecting the raw data. HRDAG is now in the unusual position of possessing a series of multiple ``snapshots'' of each group's data, collected at a number of points between 2012 and 2016. Using those snapshots, I examine how each group's data is changing over time, and discuss how those changes can impact resulting estimates of unreported deaths, showing that the changes can result in estimates for a single governorate that vary by nearly 100,000. In addition, I take advantage of the large number of processed cases to assess the performance of a variety of classification algorithms in determining whether two records refer to the same individual.