Luker, Data Reduction & CAQDAS

I apologize if my blogs about blogs are becoming redundant but I was quite taken by an active blog produced by Dan Hirschman, a PhD candidate at the University of Michigan. In his About This Blog section, he describes his academic and research interests as follows: I am a PhD candidate at the University of Michigan in Sociology and the certificate program in Science, Technology and Society (STS). Broadly, I am interested in economic sociology, the sociology of economics, organizations, and science studies. Specifically, I am interested in the interaction of quantification, law, organizations and knowledge-production. His research interests are multidisciplinary and I couldn’t help but wonder how his inquiries would be framed in and influenced by the context of an information science degree here at the iSchool.

In any case, I came to know this blog by searching for reviews of Luker. While I agree with much of what she says and find her analogies quite plausible, I was looking to come to an understanding of what graduate students at other institutions and from other disciplines felt about her work. In a post devoted to his reaction to Salsa Dancing into the Social Sciences, a methods book that he claims not only to have read but to have devoured, he raises key insights into her strengths.  He astutely expounds on Luker’s main notion of finding balance between the logic of data and the discovery of a good a research question. He also praises the fact that she sheds light on sampling, operationalization and generalization as not quite sufficient for research that aims to generate theories. This point is actually something that I grappled with while conducting my peer review assignment as the research questions posed in the paper I chose to review had mostly theoretical implications.

To draw slightly further on Hirschman’s review, he claims to not be completely in agreement with Luker’s endorsement of CAQDAS (Computer Assisted Qualitative Data Analysis, see p. 200) and Charles Ragin’s method of Boolean analysis (Qualitative Comparative Analysis – QCA) which is a method that works “out an algorithm that most economically describes the patterns observed in the data.” (Luker, 2008, p. 209) Luker argues that Ragin’s method “permits us to see both the messiness and the contingency in social life, while at the same time recognizing the patterns.” (2008, p. 213)

I understand that the algorithm recognizes patterns and is not intended to measure the messiness of life but the skeptic within does not trust its ability to make meaning out of nuance.

In any case, Luker’s chapter on Data Reduction  hones in on the intricacies of INF1240. Learning about research methods is somewhat linear however learning how to effectively use the methods and conduct data reduction in a way that allows us to “reduce our data to something we can manage, and analyze our data in meaningful ways,” (Luker, 2008, p. 198-199) is where practice and theory meet.

As a final thought, Hirschman cites one of his favourite examples from Luker and I would like to share it with you as it quite possibly may put a smile on your face:

“Librarians, along with pediatricians, are among the greatest human beings in the universe.” (Luker, 2008, p. 85)

– Vanessa K