A more considered response to mixed-methods?

This post was originally going to be my ‘more considered response to mixed-methods’, as way of introduction I wrote…

I do not think I am as anti-mixed-methods as my first reaction suggested, but I think it is going to be restricted to rather ‘buzz word’ focused research in areas such as allied health and education. After all, the qualitative/ quantitative divide is not always meaningful.

Ethnography is a broad term that can encompass a huge range of research types, but it generally means the researcher is going to actually look at the context. What I consider the ideal type of ‘old school’ ethnography, based on participant observation research, could be reinterpreted uses a range of measures. Generally people would count things (and people) and even measure things. It involves audits and reported accounts, but also it includes the experience of the researcher. The significance of and the appropriate uses of such experience have been a source of debate, and while spending so much time reflecting on the nature of the discipline can be rather dull, ultimately reflections on epistemology and sociology of knowledge within the discipline can also be used to reflect on broader contexts.

However, my more balanced enquiry came to a sudden halt when I came across an article which concludes:

‘From the standpoint of analytic alternation, qualitative (i.e., ethnomethodological or other) study of the process of converting qualitative data into quantitative form can shed light on the work involved in turning one thing into another and in justifying that work.’ (Sandelowski et al 2009: 220).

I do not think you can do the same thing with quantitizing data as you can do in survey design. This seems to be a bit of a waste of time. This is the same as microeconomic models that need ‘everything’ to be collapsed into a measure of ‘utility’. Sure such models can be useful to think with and they certainly highlight a lot about the contexts in which they are developed and used. However, such models do not predict or represent reality. It is not that I am going to vow never to read a quantitative study that collapses ‘qualitative data’ into arbitrary numbers, but I feel like my research is not going to suffer if I do not look any deeper into mixed-methods.

On a more positive note, I did read an interesting article this morning which argues that the distinctions used to separate qualitative and quantitative approaches in sociology do not hold up and that there needs to be a greater consideration of the theoretical along with the methodological (Hanson 2008).

Hanson, B. (2008). “Wither Qualitative/Quantitative?: Grounds for Methodological Convergence.” Quality and Quantity 42(1): 97-111.
Sandelowski, M., C. I. Voils, et al. (2009). “On Quantitizing.” Journal of Mixed Methods Research 3(3): 208-222.



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