Readings :: Ethnographic Decision Tree Modeling

Ethnographic Decision Tree Modeling
By Christina H. Gladwin

I picked up this slim monograph the other week (93pp.) and read it in maybe one sitting. Part of the Qualitative Research Methods series, this 1989 book proposes a modeling strategy for interpreting ethnographic data on how people make decisions:

This method is called ethnographic decision tree modeling because it uses ethnographic fieldwork techniques to elicit from the decision makers themselves their decision criteria, which are then combined in the form of a decision tree, table, flowchart, or set of "if-then rules" or "expert systems" which can be programmed on the computer. (p.8)

The author emphasizes that decision criteria should be emic, but made explicit (p.9). She notes that "people do not rank order alternatives wholistically when they make a decision. They just choose one of several alternatives without ranking them" (p.10, citing Kahnemann & Tversky, Shoemaker, Quinn, and Arrow). Thus her approach is not linear, but rather context-sensitive, testing the interpretation of an observed behavior (p.11). Thus the ethnographic data collection can take from a few weeks up to two years, and model testing can take up to 6 months (p.13). These models, like model trains, are simplified (p.13).

When we get into the models, however, we find that there's a lot of craftwork and tacit knowledge involved. In an extended case study — how students decide whether to buy a meal plan at their dorm — she models the results of each interview, then combines them, telling us to "combine them in a logical fashion while preserving the ethnographic validity of each individual decision model" (p.39, her emphasis). Okay. The models also assume a lot about both decisions and justification, primarily by portraying branching pathways with yes/no decisions.

I like modeling qualitative data, so I can see value in this modeling process. It's a good way to aggregate messy data and see patterns that may not be visible in raw interviews. However, I do worry that these "model trains" may not take us very far: they attempt to rationalize decisions that are potentially much more complicated, and they appear to rely on untriangulated interviews, meaning that they represent what people say or recall or reconstruct about their decision making. 

Nevertheless, used judiciously, this modeling technique could be really helpful. I'll keep this book in mind in case I need to model decisions in the future. If you're interested in modeling qualitative data in this way, please do pick up this book.