Insightful Discussion on Operationalization

Admittedly, thus far in the course readings I have preferred Luker's readings to Knight's. This is not to suggest that a favourite must be selected, but I sometimes find Knight to be so heavy in theory that it can be challenging to grasp the main points of his chapters (although after a few attempts I usually get there). This week, however, I found both readings to be helpful and complemented each other well.

I found Luker's chapter "On Sampling, Operationalization, and Generalization" especially insightful this week. Luker discusses in the section on operationalization that home something is defined or named is very important (which I think we all recognize), but in particular for researchers. She demonstrates this by using as an example rape statistics in the United States by providing four different estimates of the number of rapes that occur each year (from 102,560 to 683,000). If considered individually, all of the statistic numbers provided in the chapter are certainly significant and may not otherwise be questioned. But when considered together, as four different statistics on the same topic, one would automatically question why there is such a discrepancy. This demonstrates that what is considered part of a statistic depends on how researchers and respondents operationalize a particular term. One of the reasons this section of the chapter really made me pause and think after I read it was because it clearly demonstrates the power of the researcher and the responsibility that this entails. When researchers prepare questions to ask respondents, they (we) must think about our definition of a term, and how different people would define and interpret the term because this can drastically change the results.