Once the vast array of biological algorithms can be harnessed to a reasonable sociological IO system, Abbott's empiricist sequence resemblance techniques should become a reasonable tool. The major problem then will be to think through ways of combining Heise's elegance of description, Abell's rigor of homomorphic classification, and Abbott's empirically practical use of metric techniques. Unsolved too, are the great difficulties of developing a serious measurement and statistical theory for sequence analysis. All these methods at present are largely heuristic. Only now are the biologists really facing the problems of statistical inference with sequences, problems which differ in many ways from the kinds of inferences sociologists may wish to draw.
Sequence analysis holds great promise for sociology.
Most of our classic theories are sequential or interactional theories. The new methods address those theories directly. What the field needs now are junior scholars committed to exploring what sequence regularities can tell us about social life. The methods will not, to be sure, solve the great problems represented by interactional fields - where all sequences are mutually dependent and data are bewilderingly complex. But they will provide us with far more effective ways of analyzing life courses, careers, and other such relatively independent and regular sequences, ways of analyzing that accord directly with the canonical theoretical apparatus of the discipline.