Operationalization Choices

In discussing conceptualization, I frequently have referred to operationalization, for the two are intimately linked. To recap: Conceptualization is the refinement and specification of abstract concepts, and operationalization is the development of specific research procedures (operations) that will result in empirical observations representing those concepts in the real world.

As with the methods of data collection, social researchers have a variety of choices when opera-tionalizing a concept. Although the several choices are intimately interconnected, I've separated them for the sake of discussion. Realize, though, that operationalization does not proceed through a systematic checklist.

Range of Variation

In operationalizing any concept, researchers must be clear about the range of variation that interests them. The question is, to what extent are they willing to combine attributes in fairly gross categories?

Let's suppose you want to measure people's incomes in a study by collecting the information from either records or interviews. The highest annual incomes people receive run into the millions of dollars, but not many people get that much. Unless you're studying the very rich, it probably won't add much to your study to keep track of extremely high categories. Depending on whom you study, you'll probably want to establish a highest income category with a much lower floor—maybe $ 100, 000 or more. Although this decision will lead you to throw together people who earn a trillion dollars a year with paupers earning a mere $100, 000, they'll survive it, and that mixing probably won't hurt your research any, either. The same decision faces you at the other end of the income spectrum. In studies of the general U.S. population, a bottom category of $5, 000 or less usually works fine.

In studies of attitudes and orientations, the question of range of variation has another dimension. Unless you're careful, you may end up measuring only half an attitude without really meaning to. Here's an example of what I mean.

Suppose you're interested in people's attitudes toward expanding the use of nuclear power generators. You'd anticipate that some people consider nuclear power the greatest thing since the wheel, whereas other people have absolutely no interest in it. Given that anticipation, it would seem to make sense to ask people how much they favor expanding the use of nuclear energy and to give them answer categories ranging from " Favor it very much' to " Don't favor it at all."

This operationalization, however, conceals half the attitudinal spectrum regarding nuclear energy. Many people have feelings that go beyond simply not favoring it: They are, with greater or lesser degrees of intensity, actively opposed to it. In this instance, there is considerable variation on the left side of zero. Some oppose it a little, some quite a bit, and others a great deal. To measure the full range of variation, then, you'd want to operational-ize attitudes toward nuclear energy with a range from favoring it very much, through no feelings one way or the other, to opposing it very much.

This consideration applies to many of the variables social scientists study. Virtually any public issue involves both support and opposition, each in varying degrees. Political orientations range from very liberal to very conservative, and depending on the people you're studying, you may want to allow for radicals on one or both ends. Similarly, people are not just more or less religious; some are positively antireligious.

The point is not that you must measure the full range of variation in every case. You should, however, consider whether you need to, given your particular research purpose. If the difference between not religious and antireligious isn't relevant to your research, forget it. Someone has defined pragmatism as " any difference that makes no difference is no difference." Be pragmatic.

Finally, decisions on the range of variation should be governed by the expected distribution of attributes among the subjects of the study. In a study of college professors' attitudes toward the value of higher education, you could probably stop at no value and not worry about those who might consider higher education dangerous to students' health. (If you were studying students, however...)