Publications

JJ Dyck, S Pearson-Merkowitz, and Michael Coates. 2018. "Primary Distrust: Political Distrust and Support for the Insurgent Candidacies of Donald Trump and Bernie Sanders in the 2016 Primary". PS: Political Science & Politics 51 (2): 351-357.
https://doi.org/10.1017/S1049096517002505.
M Coates, and Shanna Pearson-Merkowitz. 2017. "Policy Spillover and Gun Migration: The interstate dynamics of state gun control policies". Social Science Quarterly 98 (2): 500-512.
https://doi.org/10.1111/ssqu.12422.

Education

PhD, Government and Politics

University of Maryland
College Park, MD

Specialization: Research Methodology and Political Psychology

Employment

Research Analyst @ CILSS

Largo, MD

The Center for Innovation in Learning and Student Success (CILSS) serves as the research and development wing of UMUC. As an analyst, I support the center's research mission of evaluating the University's policies and practices to improve student outcomes. My duties range from website and graphics design to implementing machine learning techniques for predictive analysis. I also look for new statistical tools and techniques that can be leveraged in our work.

Graduate Assistantship @ UMD

College Park, MD

As part of my funding agreement with the University of Maryland during my PhD, I worked on an assignment by assignment basis. While the duties varied depending on the assignment, for the most part they included instructing undergraduate students and program development.

Working Papers

Cornering the Market: Regulation Evasion as Service.

Geospatial case study that uses point-pattern analysis and quadrats to explore geographic and political variation along state borders. Public licensing data is used to explore the distribution of businesses licensed to sell firearms. This distribution is then compared to that of other business types to find patterns indicating a purposeful evasion of regulations.

Hijacking Identities: How Identity Threats Induce Tribalism.

Dissertation — Social identities like religion, race/ethnicity, and age have become reliably predictive of our political affiliations. Americans are interacting with people outside their political party less often, but why? My dissertation explores the nature of threat and how it induces tribalistic identity responses. Over time, these responses codify to produce well-sorted sociopolitical identities which are increasingly sensitive to group processes.

Skills and Experience

Programming Languages

  Python, C#

  R, SAS, SQL

  C/C++, Fortran

  HTML/CSS3/JS/PHP

Subject Areas

  Political Psychology

  Political Behavior

  State & Local Politics

  Institutions

Data Analysis

  OLS/GLM/Time Series

  Bayesian Inference

  Machine Learning

  Neural Networks

  Computer Vision, AI