whether to emulate basic principles in quantitative social sciences in establishing standards of evidence for qualitative work
Pointing to the perduring problematic between micro-level observations of case-study research and the scientific quest for empirical generalizability, Small laments that qualitative researchers often talk but don’t walk quantitative principles of validity and representativeness, “constructing sticks-and-leaves airplanes that will never fly” (2009: 11).
Small gives two examples in which qualitative researchers adopt the language of statistics and counters these with two alternative approaches – ignoring the problem is not always an option, alas (but see p18-19):
1. Extending the extended case method (e.g. Burawoy 1998)
This involves generating hypotheses (which require further testing) based on “logical inferences”, i.e. making predictions based on observed processes that take the form of statements such as: “When X occurs, whether Y will follow depends on W” (Small 2009: 24). In contrast, Small argues that hypotheses based on statistical inferences (“All entities of type A will exhibit characteristic Z”, p24) are pointless in single-case research.
The power of this method lies in the empirical knowledge it produces, namely ontological statements (Small 2009: 26):
a well executed single-case study can justifiably state that a particular process, phenomenon, mechanism, tendency, type, relationship, dynamic, or practice exists (…). This, in fact, remains one of the advantages of ethnographic work, the possibility of truly emergent knowledge.
2. Sequential interviewing
This solution holds that (Small 2009: 25)
case study logic can be effectively applied to in-depth interview-based studies, such that the latter may be conceived as not small-sample studies but multiple-case studies
This solution draws on Yin’s theory of sequential case study research. The goal here is to reach a level of saturation: each new case study adds a layer of insight until very little new information is generated.
Small (2009: 29) concludes that both alternative approaches
call for logical rather than statistical inference, for case rather than sample-based logic, for saturation rather than representation as the stated aims of research. The approaches produce more logically sensible hypotheses and more transparent types of empirical statements.
So then, this is one way ethnographers can engage with critiques from scholars with a more quantitative bent. In my own research, I am faced with the methodological challenge of incorporating different epistemological data sets (quantitative and qualitative). I too tend to rely on “statistical language” when addressing methodological concerns. Viewed through a quantitative lens, case studies lose much of their sex appeal. Yin’s approach to case study research (ahem) brings sexy back.
Small, Mario Luis (2009). ‘How many cases do I need?’: On science and the logic of case selection in field-based research. Ethnography 10 (1): 5-38.