Luker 2008



Keywords: luker 2008
Description: Yesterday, I picked up from the library a copy of Salsa Dancing into the Social Sciences, a newish (2008) methods book by UC Berkeley sociologist Kristin Luker. I just finished reading -or perhaps more accurately "devouring" - it. Luker does something (really several things) I've been looking for ever since I started graduate school but…

Yesterday, I picked up from the library a copy of Salsa Dancing into the Social Sciences. a newish (2008) methods book by UC Berkeley sociologist Kristin Luker. I just finished reading -or perhaps more accurately “devouring” – it. Luker does something (really several things) I’ve been looking for ever since I started graduate school but never seen done well and manages to produce an incredibly fun, readable, and useful text, at least for someone like me. Salsa Dancing is not for everyone (much as salsa dancing is not for everyone, including me!). Luker’s book is specifically aimed at scholars doing “non-canonical”, usually qualitative research. And indeed, I think her division of the world of social science (really, sociology) research into two camps is one of the single most useful contributions of the book. This division is not based on methodology, in the old sense of “kind of data”, but rather in the kind of questions we are asking – and Luker argues that the non-canonicals have a lot of learn from the canonicals, and a lot to learn about how to talk to them and convince them of the value of our work.

So, what are canonical and non-canonical social science? Here’s how Luker describes the difference:

[C]anonicals want to know the distribution of a population among known categories. as estimated from a properly drawn sample with a known error factor. We salsa-dancing researchers, on the other hand, want to discover the relevant categories at work. not the distribution of some larger population across categories that we have a priori chosen. We have turned to our kind of research because we have a question that canonical social science can’t take on, or can’t take on very well. (p. 102)

Note here that the difference is not simply in what kinds of data the researcher draws on – surveys vs. interviews vs. fieldwork vs. archives etc. – but rather in the kind of questions that puzzle us. Luker emphasizes how canonical research is grounded heavily in a logic of verification, while salsa-dancers are (or ought to be) grounded in a logic of discovery. The problem is that until now, there have been relatively few “good” places for non-canonicals to go for rigorous advice on methodology.

What do I mean by good? One of the most compelling parts of Luker’s book is the way she seamlessly weaves together insights from the history of social science and methodology, especially Foucauldian and science studies perspectives, along with practical advice. Luker quickly traces the history of the large scale survey, and how before WWII, quantitative work in Sociology was gendered feminine and associated with activists like Jane Addams (who was in fact on faculty at Chicago, and published in AJS frequently). With the rise of the large-scale survey, and the infusion of government and foundation money into the practice (“governmentality” much?), the gender of quantitative work switched rapidly, and the older model of verstehen and all that fell out of favor. Luker tells this story to get across a key finding from the Foucauldian/post-y perspective – all methods are problematic, all methods are tied to power dynamics, and so on. But, that doesn’t mean that the folks doing quantitative, canonical work are mindless cultural dopes fulfilling their role in the state apparatus. And in many ways, because there has been so much work put into canonical sociology, salsa-dancers have a lot of catching up to do.

Luker focuses on three interrelated aspects of canonical methodology that non-canonicals have to pay attention to, and have to do figure out how to do differently: sampling, operationalization and generalizability. Luker’s point is that canonical methodology works well to answer these three concerns for canonical problems – the relationships between pre-given categories. For research that aims to generate theories – and to generate lists of relevant categories rather than conditional correlations between variables – these problems must be solved differently.

So, rather than producing a random sample from an exhaustive (or nearly) frame of everyone you wish to generalize about, salsa-dancers should seek out “data outcroppings”, rich sites where the dynamics of interest should be easiest to see. Unfortunately, such sampling can (just as canonicals always allege) create a problem of bias that weakens generalizability. The non-canonical researcher relies on a logical generalizability rather than a statistical one – e.g. I have no reason to think that the public school I studied in my fieldwork is different from most other schools in ways that would affect my findings, and I put the burden on your to show me what I have logically missed. Having a few cases, or at least a shadow comparison, can help with this sort of argument. Luker also pushes us to generalize up, rather than across – not simply generalizing to all sites similar to where we do our fieldwork, but to broader kinds of problems (“how classes reproduce themselves without seeming to” p. 126).

So, Luker does a great job on the theoretical (establishing a framework for understanding the discipline of sociology and how it got to be arrayed the way it is, and then for figuring out which kind of research you want to be doing) and the broadly methodological (thinking about case selection, constantly asking “what is this a case of?”, considering sampling, operationalization and generalizability on our own terms). She also has tons of nuts and bolts practical tricks – ways to think about coding interviews, or gaining entree to a research site, or organizing an interview to elicit (including, for example, embracing leading questions as useful ways to elicit responses and push-back from interviewees, rather than eschewing them as is done in canonical survey research, p. 177). She also writes like someone who actually cares about how easy and fun it is to read her book, and it makes a huge difference. From the salsa-dancing metaphor running throughout the book (which is also practical advice about the virtues of unfamiliar physical activity as a way to relieve anxiety and open up your mind), to hilarious asides*, the book is just eminently enjoyable. It’s also very tight – just 225 pages plus appendices and bibliography. If I were teaching a research methods class**, I’d probably assign the whole thing or almost all of it.

A few parting thoughts. One, I’m not wholly convinced by the discussion of Ragin’s Qualitative Comparative Analysis (QCA), which Luker discusses in glowing terms. But I haven’t read the original, and I’m now at least interested enough to go check it out. Two, for someone with some background in historical research, a lot of what Luker discusses feels familiar. I think this is actually a strength, not a weakness. Luker comes out and admits in a chapter on comparative and historical work that many of her ideas come from comparative and historical sociology, and she argues that most comp/hist sociologists (if not all) are already salsa-dancers. But she goes on to say that they learned the tricks of their trade through trial-and-error and apprenticeship; there is no good go-to text. I think she’s right about that, and I think her book will be an excellent tool for bridging the gap between what comp/hist folks know they want to do and helping them figure out how to do it. More importantly, I think this book will help qualitative/fieldwork/interview-based scholars who are non-canonical find historical allies and build a common methodological language – rather than attempting to shoehorn their work into the independent/dependent variable model inherited from the canonical folks.

In summary, Salsa Dancing is a fantastic book for anyone who wants to do non-canonical social science, or teach others how to do it.

* Two favorite examples: On librarians: “Librarians, along with pediatricians, are among the greatest human beings in the universe.” (85) On content analysis and its history: “Paul Lazarsfeld (who seems to have invented almost every social science method known to humans in his spare time) and Harold Lasswell laid out the framework for doing content analysis as long ago as the 1920s and 1930s.” (187)

** More specifically, if I were teaching a graduate research methods class. I am actually GSI-ing (TAing) an undergrad methods class in the Fall.






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