Speaker
Description
At least three, partially overlapping research frameworks are commonly employed in studies of spatial health data: the risk factor, neighborhood effects, and "formal causal inference" frameworks. These share an important but limited objective: to produce discrete effect estimates. Case studies are a broad class of study designs that involve narrative forms of argument, multiple sources of data, and often an investigative, place-based mode of research. What resources might qualitative and case-based methodologies provide for spatial data analyses? Here, I engage with Michael Burawoy's extended case method for ethnography and ask how it might contribute to quantitative research. I consider if and how each of Burawoy's four core concepts (his "extensions") may be turned into questions that can be posed in order to situate small-area health data within a social context that extends outward in time and space. This presentation will introduce these ideas via an ongoing study of colorectal cancer (CRC) inequalities in the urbanizing regions surrounding Dallas-Fort Worth and Houston, Texas. The study situates the evolution of the CRC burden over recent decades in concurrent transformations of urban space, demography, livelihoods, and preventive technology. Rather than search for replicable or representative findings, the study is most concerned with learning of, and learning from, the distinctive features of the study areas. Overall, this presentation will discuss how incorporating qualitative and reflexive 'casing' techniques may help to enrich spatial analyses of quantitative health data.
