Christopher Fariss

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My core research focuses on the politics and measurement of human rights, discrimination, violence, and repression. I use computational methods to understand why governments around the world torture, maim, and kill individuals within their jurisdiction and the processes monitors use to observe and document these abuses. Other projects cover a broad array of themes but share a focus on computationally intensive methods and research design. These methodological tools, essential for analyzing data at massive scale, open up new insights into the micro-foundations of state repression and the politics of measurement.

People rely more on strong ties for job help in countries with greater inequality. Coefficients from 55 regressions of job transmission on tie strength are compared to measures of inequality (Gini coefficient), mean income per capita, and population, all measured in 2013. Gray lines indicate 95% confidence regions from 1000 simulated regressions that incorporate uncertainty in the country-level regressions (see below for more details). In each simulated regression we draw each country point from the distribution of regression coefficients implied by the estimate and standard error for that country and measure of tie strength. P values indicate the simulated probability that there is no relationship between tie strength and the other variable. Laura K. Gee, Jason J. Jones, Christopher J. Fariss, Moira Burke, and James H. Fowler. “The Paradox of Weak Ties in 55 Countries” Journal of Economic Behavior & Organization 133:362-372 (January 2017) DOI:10.1016/j.jebo.2016.12.004