Happy Fourth of July! Philadelphia hosts a huge free concert and festival, with lots of big-name artists: Ed Sheeran, Nicki Minaj, and Jennifer Hudson, to name a few. Despite some rain in the morning, it was a beautiful evening.
Over the holiday weekend, I also took advantage of Free First Sunday to visit the Barnes Foundation, a museum with a formidable collection of Impressionist and Modernist paintings. Once again, I’m grateful to have the opportunity to explore Philadelphia beyond the daily rhythms of my internship.
At my work with Research for Action, I’m becoming increasingly familiar with the organization’s various research methods. Last week, I learned how to code data using Atlas.ti, a software program for qualitative data analysis. I’ve then been continuing with my cross-year analysis, examining developments and trends across the first three years of RFA’s study. Interning with RFA has led me to consider the importance of mixed-methods social research, which employs both quantitative and qualitative methods to gain both depth and breadth of understanding.
My appreciation for qualitative research was also fostered by the CPGC intern retreat in April, during which Dr. Stephen Danley of Rutgers (danley.rutgers.edu/) spoke on the importance of local knowledge in shaping urban policy. Dr. Danley is vehemently opposed to large-scale quantitative studies such as the randomized control trial, the experimental model that has become the “gold standard” in social research. Instead, he argues that research should be guided by a more equal and informal relationships between researchers and citizens, allowing communities to shape their own research and policy agendas. Dr. Danley’s philosophy is, to some degree, at odds with my work at Research for Action, where the large-scale randomized trials have played a consistent role in our mixed-methods studies. Rather than discount either research practice, however, I have come to understand the two styles as complementary rather than contradictory: mixed-methods research recognizes the scientific rigor of the large-scale quantitative study, while still honoring the depth and nuance of qualitative research.