Association for Public Policy Analysis & Management

This presentation provides a dual perspective on the other two panel papers, problematizing and contextualizing some of the findings, and then describing one collaborative solution to these challenges, which we are currently pursuing with the NYC Partnership for College Readiness and Success.

I describe in this presentation the range of ways that Goddard Riverside Options Center has used the Research Alliance findings to compare the population that we serve against the city more broadly. I also describe some of the challenges of using the categories of SES as described here—both Free/Reduced Lunch eligibility and the median neighborhood income measure. Specifically, the population of students we serve are almost exclusively in the lowest categories of SES, which means that we are unable to differentiate at the level of granularity that we need to be responsive from a programmatic perspective. CUNY’s focus on Expected Family Contribution is a particularly welcome development as it identifies quite precisely the students we are most likely to serve, namely those with zero EFC and absolutely no elasticity in their family income. We also describe here some of the areas that CBOs like Options are best-positioned to illuminate—the experiences of undocumented students, for instance, which CUNY notes as a blind spot.

The data challenges that all three of our papers describe are, in some ways, indicative of the larger divide between research and practitioner spheres in New York City and elsewhere. While our organizations are committed to using data to track programmatic outcomes and improve programs, we are often limited by a variety of logistical concerns, including insufficient infrastructure for securing and storing private student data and insufficient time for the lengthy process of tracking student outcomes. For most organizations like ours, these activities pull time and resources away from our primary mission to serve students.

Even more problematic, our services are often completely invisible to researchers working in other institutions in the city. Which students we serve, the nuances of the challenges they face, and their experiences with bureaucracy and other institutional barriers—these are pieces of information that we feel are essential for understanding the college landscape. We also know from anecdotal evidence in the field that CBOs are supporting the implementation of important institutional interventions at both CUNY and DOE—work that we have come to think of as “the village effect.” And our contributions to these larger initiatives are also often invisible.

In response to some of these challenges, we have recently established a data collaboration with the members of the New York City Partnership for College Readiness and Success. As of this fall, we will be piloting this data collaboration project with four other college access organizations in the city. The data hub will link the relational administrative database housed at the Research Alliance with our individual programmatic data, in the hopes of providing the CBOs more efficient access to data about their students’ academic histories and outcomes, and our partners with detailed programmatic information that would be otherwise unavailable.