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Recruiting is a way of understanding university enrollment priorities. University responses to addressing access inequality has largely focused on adopting policies like holistic admissions and need-based financial aid (White House, 2014), but scholarship on organizational behavior shows that formal policies often represent symbolic rather than substantive efforts (e.g., Davis, 2005). University recruitment is a substantive effort that can yield insights about university enrollment preferences. For example, universities that care about enrolling low-income students and students of color will recruit from high schools and communities with large numbers of these students. On the other hand, universities that care about enrolling upper-middle class, white students will recruit within affluent white communities. Unfortunately, scholarship on recruiting is rare because recruiting data are difficult to obtain.
My dissertation overcomes this problem by using data science methodologies to collect off-campus recruitment visits to high schools, community colleges, and communities. I aim to answer what are the characteristics of schools and communities that receive recruitment visits from public universities versus those that do not? Many universities advertise off-campus recruiting events on admissions websites. Additionally, universities often promote recruiting events on Twitter. I have written programs to “scrape” off-campus recruitment events from admissions websites and programs to stream Tweets posted on Twitter to collect data on which schools and communities recruiters are visiting. I merge these recruiting data to secondary data on high schools, community colleges, and communities. My dissertation applies regression and geospatial analyses to these events to understand the racial, socioeconomic, and academic achievement characteristics of high schools and communities that receive visits by admissions recruiters and those that do not.