Project Description
This summer’s research will build on research done with SRS students last summer, laying the groundwork for my new project on cynicism and distrust in public life. This summer, we will use a variety of machine learning models to explore patterns of distrust and cynicism in global public opinion, focusing on World Values Survey data (https://www.worldvaluessurvey.org), joined with country and country-year data from a variety of sources (UN Human Development Reports, the World Bank, and more). This will include using random forest models to predict individuals’ trust responses and then using these models to select important features for explanatory modeling. We will also use generalized additive models (GAMs) to explore patterns of interest to the PI and to student researchers, as appropriate. Questions to explore include the relationship between measures of institutional functioning and (dis)trust, population heterogeneity and (dis)trust, and economic performance and (dis)trust).
Prerequisites
Some prior experience working with applied data science (R or Python) is expected. It would be ideal if student researchers already have some fluency with basic wrangling and data visualization using the tidyverse suite in R.
Exposure to social science theory (e.g., sociology, anthropology, political science, economics) would be helpful.
If applicants have questions about their preparation in these respects they are encouraged to reach out to the professor.
Special Comments
Students with otherwise strong credentials but who don’t have prior R experience could satisfy this requirement by enrolling in the professor’s 1-credit “R for Social Scientists” course in winter, 2025.
Project Information (subject to change)
Estimated Start Date: 6/16/2025
Estimated End Date: 7/25/2025
Estimated Project Duration: 6 weeks
Maximum Number of Students Sought: 3
Research Location: On campus
Contact Information: Jon Eastwood (email: eastwoodj@wlu.edu)