Enemies Within: Labeling Defectors to Rival Authorities
How do allegiances shift from incumbent rulers to rival authorities?
From rebel groups to state authorities, political actors take extreme measures to ensure the loyalty of their subjects.
Those who are labeled as defectors or 'traitors' may be ostracized, imprisoned, tortured or killed.
But the expected consequences of such punishments remain disputed by an established body of scholarship on state repression,
civil wars, and criminal behavior. Either the labeling of people as defectors deters undesirable behavior,
leading to widespread conformity with rules set by authorities.
Or it intensifies defection from political orders, as the labeled shift support to rival authorities who support their behavior.
This project relies on a mixed-methods approach to investigate shifts between conformity and defection in the former
German Democratic Republic and the Occupied Palestinian Territories, drawing on archival research, an original lab experiment, semi-structured interviews,
existing survey data, and an empirically validated computational model.
Modeling Early Risk Indicators to Anticipate Malnutrition
MERIAM was a four-year project funded by the UK government, which brought together an inter-
disciplinary team of experts across four consortium partners: Action Against Hunger, the Graduate
Institute of International and Development Studies, John Hopkins University, and the University of Maryland.
MERIAM’s primary aim was to develop, test and scale-up models to improve
the prediction and monitoring of undernutrition in countries that experience frequent climate
and conflict related shocks.
Among my tasks were the co-development of an evidence-driven computational model,
implementation of the model in Python, data construction and analysis, the coordination of the research project,
the implementation of expert interviews, as well as focus group discussions
and a survey during two weeks of fieldwork in Uganda and Kenya.
The project was funded through a research grant awarded to the Center for International Development and Conflict Management
at the University of Maryland. It evaluated the association between development aid and the likelihood,
escalation, severity, spread, duration, and recurrence of violence, spanning the phases before, during,
and after conflict.
I assisted on the project during its final phase.
My primary task was to construct and visualize geo-coded resilience indices from various conflict datasets.