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IT PAYS TO TAKE SAMPLES AND TO STICK WITH THEM

If you are doing all the work yourself, it’s next to impossible to interview more than a few hundred people. Even in a community of just 1,000 households, you’d need several interviewers to reach everyone. Interviewers may not use the same wording of questions; they may not probe equally well on subjects that require sensitive interviewing; they may not be equally careful in recording data on field instruments and in coding data for analysis. The more personnel there are on any project, the greater the instrumentation threat and the more risk to the validity of the data.

Most important, you have no idea how much error is introduced by these problems. A well-chosen sample, interviewed by people who have similarly high skills in getting data, has a known chance of being incorrect on any variable. (Careful, though: If you have a project that requires multiple interviewers and you try to skimp on personnel, you run a big risk. Overworked or poorly trained interviewers will cut corners; see chapter 8.)

Furthermore, studying an entire population may pose a history threat to the internal validity of your data. If you don’t add interviewers, it may take you so long to complete your research that events intervene that make it impossible to interpret your data.

For example, suppose you are interested in how people in a community feel about being relocated in anticipation of a new dam coming on line and their land being flooded. You decide to interview all 210 adults in the community. It’s difficult to get some people at home, but you figure that you’ll just do the survey, a little at a time, while you’re doing other things during your year in the field.

About 6 months into your fieldwork, you’ve gotten 160 interviews on the topic—only 50 to go. Just about that time, the courts adjudicate a particularly sore point that has been in dispute for a decade regarding access to a particular sacred site. All of a sudden, the picture changes. Your ‘‘sample’’ of 160 is biased toward those people whom it was easy to find, and you have no idea what that means. And even if you could now get those remain?ing 50 informants, their opinions may have been radically changed by the court judgment. The opinions of the 160 informants who already talked to you may have also changed.

Now you’re really stuck. You can’t simply throw together the 50 and the 160, because you have no idea what that will do to your results. Nor can you compare the 160 and the 50 as representing the community’s attitudes before and after the judgment. Neither sample is representative of the community.

If you had taken a representative sample of 60 people in a single week early in your fieldwork, you’d now be in much better shape because you’d know the potential sampling error in your study. (I’ll discuss how you know this later on in this chapter.) When historical circumstances (the surprise court judgment, for example) require it, you could interview the same sample of 60 again (in what is known as a panel study), or take another representative sample of the same size and see what differences there are before and after the critical event.

In either case, you are better off with the sample than with the whole population. By the way, there is no guarantee that a week is quick enough to avoid the problem described here. It’s just less likely to be a problem.

 
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