Because Andrew Abbott’s use of the term “heuristics” in the subtitle to Methods of Discovery (or perhaps just my clumsy presentation of it), I thought it might be worthwhile to flesh out a bit what Abbott means by the term and why he thinks that heuristics are important. First, then,
Most modern writing about heuristic comes from mathematics. Mathematicians often have particular problems to solve: how to solve the normal distribution integral (hint: you can’t do it analytically), how to create a perfect pentagon, how to categorize all the possible types of disconnection in six-space, and so on. Mathematicians often know or suspect the answer they seek but need to be sure of how one gets there. Even when they don’t know the answer, the usually have a clear idea of what an answer looks like. In such a context, heuristic means thinking creatively about how to get from problem to solution. Often one builds out from the problem on the one hand and from the solution on the other until the two halves meet in the middle like a bridge built from two banks.
How to get from here to there, in a situation where there may be multiple routes to choose from. That sounds good to me. A page later, Abbott turns from mathematics to the social sciences.
In the social sciences we often have a different situation. We often don’t see ahead of time exactly what the problem is, much less do we have an idea of the solution. We often come at an issue with only a gut feeling that there is something interesting about it. We often don’t know even what an answer ought to look like….Most teaching on methods assumes that the student will start a research project with a general question, then narrow that to a focused question, which will dictate the kind of data needed, which will in turn support an analysis designed to answer the focused question. Nothing could be further from reality. Most research projects—from first-year undergraduate papers to midcareer multiyear, multi-investigator projects—start out as general interests in an area tied up with hazy notions about some possible data, a preference for this or that kind of method, and as often as not a preference for certain kinds of results. Most research projects advance on all of these fronts at once, the data getting better as the question becomes more focused, the methods more firmly decided, and the results more precise.
The upshot is that a trained ability to envision different possible outcomes and different routes to reach them — to think in terms of heuristics—is a valuable skill. Given my personal experience, that sounds right to me.