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Research Assistant - Illuminating the Relationship between Social Capital and Social Infrastructure

Seeking quantitative-skilled graduate student (R or Stata, see more below) with deep familiarity with social science and the concepts of social capital, social infrastructure, and resilience. Along with conducting research with Prof. Aldrich, the graduate student will spend at least two hours per week working on developing the skills of the undergraduates and the faculty member will have a lab meeting with the full team every two weeks. Depending on the abilities of the undergraduate student(s), we have a number of training areas in mind, including ethical considerations for data collection and the IRB process, research design and structure, data collection methods, statistical analysis of real world dataset. We hope to engage in basic programming in R/Python to equip undergraduate students with skills in collecting digitized data, structuring digitized data, and handling data formats. In the area of quantitative methods we hope to teach how to generate descriptive statistics, hypothesis testing, cross tabulation, bivariate regression and correlation and multiple regression. Ideally we will familiarize our undergraduate students with several statistical platforms including R, Python, Stata, and SPSS. Finally, should time permit (such as over the fall semester for students interested in continuing), we would like to introduce advanced quantitative techniques such as logistic regression, missing data imputation, machine learning, and the utilization of GIS. Aldrich has extensive experience working with undergraduate students on methods both from classroom experience, past multigenerational team experience, and also from the Aldrich Resilience Lab.

  • Location:

    Boston / online

  • Remote Work:

    Yes

  • Semester:

    Summer 2025

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  • Project Title

    Illuminating the Relationship between Social Capital and Social Infrastructure

  • Faculty / Project Lead

    Daniel Aldrich

  • Project Description

    Social infrastructure- the places and spaces where we built ties and connections, such as libraries, parks, and pubs- provides a location for residents to build trust and networks outside of homes and workplaces. But its relationship with social capital- the ties that connect us to others- remains unclear. What types of locations best create connections? What are the qualities of “good” rather than “poor” social infrastructure? Do all social infrastructure facilities generate and maintain the same types of connections? Do certain underrepresented groups have the same access to and use patterns of these facilities? The faculty (Aldrich) and graduate student (TBD) will work together carrying out research, data collection, cleaning, and analysis, and will also supervise undergraduates using a mixed methods approach gathering qualitative (field observations, case studies, interviews, newspaper articles, peer reviewed journal articles, books, YouTube documentaries) and quantitative (budget investments, resilience indicators, census data, American Community Surveys information, survey responses) data on social capital and social infrastructure. Then, the team will carry out multimethods analysis using the data, including case studies, regression, heuristic text analysis and process tracing.

  • Qualifications Necessary

    Seeking a graduate student with the following skillsets: 1) Familiarity with advanced regression and analytical techniques for the social sciences, including difference in difference, time series, cross sectional, and coarsened exact matching (CEM) 2) Comfort teaching undergraduates data collection, data curation and cleaning, and statistical methods using R 3) Ability to self-motivate and work independently on complex projects

  • Hours per Week

    20 Hour Position