FOLBRE--D. WILSON

Though this article made many points, it articulated early on the tension that can arise between ethnography and “scientific” research design. Ethnographers can encounter difficulty in translating their findings into a form that other researchers or social scientists want to use—translation that usually involves quantifying research, which can take away from the responses. Consider a survey on patient satisfaction—the most common questions require respondents to rate interaction with health care providers via numerical scales or to note their average wait time for an appointment. What information is lost about the patient’s experience in using this survey to measure satisfaction? Writes Folbre, “Households, like decks of cards, have suits and hierarchies; their members are almost always differentiated by gender and by age” (248). One can say what they’d like about the merits of using gender and age as variables for measuring households—that they’re common characteristics that can describe any given population, that they’re enduring—but the short answer is that gender and age are incredibly easy to measure. I recently attempted to run a regression on data from a survey about the sexual life of prison inmates, but couldn’t get past the lack of continuous variables. Most of the questions called for a “yes” or “no” answer, so offered no meaningful regression, or were too open-ended to be summarized in the data analysis software we were using. Should the understanding of ethnography adjust? Or should what Kuhn terms “normal science” reconsider what its aims should be, being that many trajectories of thought are not contained in neat little survey boxes or lines of code in statistical models?

On this Folbre offers us a treasure trove: “‘scientific’ theories are based on untestable or circular assumptions. They are seldom if ever validated in any conclusive way by empirical research. Even more important, normal scientific research agendas are often limited to questions that can be answered simply by means of technical ingenuity. As Kuhn writes, ‘Normal science does not aim at novelties of fact or theory, and, when successful, finds none’” (249). So much can be lost in seeking to align with new technology—“novelties” can be put on the wayside, such are current models of what is considered success. So how do we approach this? Is there a way for our units of measurement to a more complete picture, especially with something like the household?

(Side note: If you’re interested in the study of prison inmates mentioned above, the study is “Ethno-Methodological Study of the Subculture of Prison Inmate Sexuality in the United States, 2004-2005,” found through the Inter-University Consortium for Political and Social Research. Put “ISPCR” into Google and the main site should come up—handy resource for anyone in need of data sets).