As you’re working your way through the dissertations, remember why you’re reading them: It’s not just to learn about their topics. Rather, It’s to begin to get a sense of how dissertations can be put together — how they’re written, how ‘theory’ is used; how “literatures” are reviewed, how methods are described, and so forth. Although schools try to standardize things into formulas and procedures, this learning from others’ work – and trying to do your own with help from others – is really the way you learn to do things.
But how and what do you learn from reading a dissertation – or from articles and books (not textbooks, which are generally worthless, but real texts)?
You can think of it two ways.
First, you begin to develop a repertoire of possible solutions or ‘resolution shapes’ for the problems of writing up empirical material. This is a standard approach (a form of “heuristic,” actually) best known in mathematics and the sciences. The famous math professor/teacher Georg Polya’s book “How to Solve It” [someone’s put the first chapter online here: http://www.math.uconn.edu/~ferrone/Polya_ch_one.pdf%5D – mentioned by Abbott, systematized it (I noticed searching the web for this that there are handouts summarizing the approach from many universities and departments, including physics at OSU]. This is not just something beginners do. The legendary, Nobel-prize winning physicist Richard Feynman described something analogous:
I spent a few years trying to invent mathematical things [wiggling his right hand] that would permit me to solve the equations, but I didn’t get anywhere. And then I decided that in order to do that, I must first understand more or less how the answer [gestures with the left hand] probably looks. Its hard to explain this very well, but I had to get a qualitative idea of how the phenomena works rather before I can get a good quantitative idea. [Feynman, quoted in Lave, 1988, p. 204)
Feynman is dealing with a different galaxy of problems than beginners, of course, but there’s a basic similarity in strategy, that’s completely lost in the misleading way research often taught. In many courses, the emphasis is on technique, method – a set of tools or procedures, supposedly independent of problem or topic, and applicable across contexts (bear with me here – I’ll get to the dissertations eventually!)
The anthropologist Berreman (1966) talked about this, drawing on Gladwin’s (1964) case study of how Micronesian navigators manage to sail out of sight of land without a compass (this is a big deal – no other group in world history ever did this – or at least, did so and managed to make it back home). The details of Gladwin’s study and Berreman’s article are not really important (later research shows that Gladwin got parts of the process wrong (partly for interesting methodological reasons, see Lewis’s book We the Navigators) – though not in ways that reduce the value of the illustration for my purposes, and Berreman’s argument is not actually one I entirely agree with entirely; but his summary is apt:
[Gladwin] points out that the European navigator begins with a plan – a course – which he has charted according to certain universal principles, and he carries out his voyage by relating his every move to that plan. His effort throughout his voyage is directed to remaining “on course.” If unexpected events occur, he must first alter the plan, then respond accordingly. The Trukese navigator begins with an objective rather than a plan. He sets off toward the objective and responds to conditions as they arise in an ad hoc fashion. He utilizes information provided by the wind, the waves, the tide and current, the fauna, the stars, the clouds, the sound of the water on the side of the boat, and he steers accordingly. His effort is directed to doing whatever is necessary to reach the objective. If asked, he can point to his objective at any moment, but he cannot describe his course. (Berreman, 1966, p. 347)
Berreman draws the analogy: “Scientistic . . . [researchers] are the intellectual brethren of the European navigators. They know how they are going, but often are not sure where.” The question is to what extent qualitative researchers are like or unlike Trukese. Lucy Suchman, developing the idea of “situated cognition” at Xerox Palo Alto lab in the 1980s, argued that “we all act like Trukese, however much some of us may talk like Europeans . . . because the circumstances of our actions are never fully anticipated and are continuously changing around us” (Suchman, 1987, p. ix). Experimental designs, surveys, psychometric ‘instruments,’ Likert scales, and so forth are tools that help us ‘talk like Europeans’ – that is, they obscure meanings, history, emergent phenomena, context, and the like.
Since you’re not allowed to do that in this course (and the others in the sequence) – how do you move ahead?
Well, you need some idea where you’re heading – or your destination. That has two meanings in research. One, which you’re still struggling with, is the substance of the problem you’re working on – what is it you want to learn? What is it you don’t and others don’t know? (Polya’s “unknowns,” the gaps in the literature, etc.) – in this regard you’re not quite like the Trukese sailor, since what you’re really searching for or orienting your journey around is a gap, an absence, a blank spot on the map (you might find interesting in this regard, Jon Wagner’s (1993) piece, “Ignorance in educational research, or, How can you not know that?” in Educational Researcher, 15-23.)
The other meaning of a destination refers to the form or shape that an answer can take – what the solution ‘looks like’ to use Feynman’s phrase.
That’s where the dissertations (and articles, etc.) come in: These are exemplars of what possible solutions look like. Again, this works in two ways.
First, you get an idea of how to study a certain kind of problem: interested in how racial identification processes unfold in organizations, here’s one way to study it (study a comparison set of organizations intensively, do a lot of participant observation research instead of relying on what people might tell you in an interview, etc.). Is this the only way to study racial identification in organizations? No, of course, not, so you read more, and as you do you compare, and think about what’s gained or lost, which approaches are most compelling or persuasive, and so forth.
Second, and here, finally, is what I’ve asked you to focus on in particular, you get a sense of how this kind of writing works, how such texts can be put together. Here you have to read carefully and reflectively – What does Lewis accomplish by beginning her work with those anecdotes about her own experience: How does it begin to establish an authorial voice? What image of her does it convey (and one constructs an image of oneself as a writer – it’s not a process of revealing yourself or your biases, it’s a matter of positioning yourself in a persuasive text to make it more persuasive). How are the anecdotes related to the way she introduces her problem and uses the literature in the following chapter? How does she use quotations? How does she generate questions or gaps from the literature? How does she situate her study in relation to larger societal problems? Etc.
And how does this kind of reading ultimately help you become a qualitative researcher? Well, reading these kinds of works, and theory works – and reading them not as a consumer, but as a producers, that is, analyzing how they work rather than just following the story along (you haven’t been doing that, have you?) you begin to build up a huge repertoire of possible patterns and cases that you can use in trying to make sense of your own research problems and settings. The idea of expertise here is not one where you master some jargon and procedures. Here I’ll appeal to the work of Dreyfus on expertise: They argue that experts do not follow rules or procedures, but instead think through the media of complex cases – situations – engaging in a lot of complex pattern-matching and discrimination:
The expert is simply not following any rules! He is . . . discriminating thousands of special cases. . . . This in turn explains why expert systems are never as good as experts. If one asks an expert for the rules he is using one will, in effect, force the expert to regress to the level of a beginner and state the rules he learned in school. Thus, instead of using rules he no longer remembers, as the knowledge engineers suppose, the expert is forced to remember rules he no longer uses. If one programs these rules into a computer, one can use the speed and accuracy of the computer and its ability to store and access millions of facts to outdo a human beginner using the same rules. But such systems are at best competent. No amount of rules and facts can capture the knowledge an expert has when he has stored his experience of the actual outcomes of tens of thousands of situations.
[H Dreyfus (with Stuart Dreyfus) “From Socrates to Expert Systems: The Limits of Calculative Rationality,” Philosophy and Technology II: Information Technology and Computers in Theory and Practice, Carl Mitcham and Alois Huning, Eds, Boston Studies in the Philosophy of Science Series, (Reidel, 1985).
In this regard you may recall the Forsythe article, in which she shows that the ways the diagnosticians responded with generalizations about their practice in interviews had little bearing on what they did in actual cases on rounds.
And how does this relate to learning to do research? Reading, lots of reading, is the key – and not methods texts alone, and not just ‘theory’ (although both can be useful) – but actually studies, and not just studies directly related to your particular problem, but studies related to it analogically (think of Abbott’s examples).