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Russel-Research-Method-in-Anthropology

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434 Chapter 15<br />

The results were mixed. The men found work<strong>in</strong>g on the computer-controlled<br />

mach<strong>in</strong>es more <strong>in</strong>terest<strong>in</strong>g, more satisfy<strong>in</strong>g, and more important than<br />

work<strong>in</strong>g on the manual mach<strong>in</strong>es, and they found programm<strong>in</strong>g the computercontrolled<br />

mach<strong>in</strong>es even more <strong>in</strong>terest<strong>in</strong>g than runn<strong>in</strong>g them. But these<br />

mach<strong>in</strong>ists also felt more <strong>in</strong> control when they worked on manual lathes.<br />

If you use self-adm<strong>in</strong>istered questionnaires, of course, you need literate<br />

<strong>in</strong>formants to do experience sampl<strong>in</strong>g. But, as Chick says, ‘‘with more and<br />

more anthropological research <strong>in</strong> modern and moderniz<strong>in</strong>g societies, experience<br />

sampl<strong>in</strong>g can be a valuable addition to the anthropologist’s tool kit’’<br />

(1994:6). And if you give people little tape recorders or digital recorders, you<br />

may be able to use the ES method with nonliterate populations. (For more on<br />

the experience sampl<strong>in</strong>g method, see Scollon et al. [2005]; and see Kahneman<br />

et al. [2004] for a method that duplicates experience sampl<strong>in</strong>g through direct<br />

<strong>in</strong>terviews rather than with beeper <strong>in</strong>terrupts.)<br />

Comb<strong>in</strong><strong>in</strong>g Cont<strong>in</strong>uous Monitor<strong>in</strong>g and Spot Sampl<strong>in</strong>g<br />

The difference between CM and spot sampl<strong>in</strong>g is analogous to the difference<br />

between ethnography and survey research. With ethnography, you get<br />

<strong>in</strong>formation about process; with survey research, you get data that let you estimate<br />

parameters for a population. Spot sampl<strong>in</strong>g is used <strong>in</strong> TA research precisely<br />

because the goal is to estimate parameters—like how much time, on<br />

average, women spend cook<strong>in</strong>g, or men spend throw<strong>in</strong>g pots, or children<br />

spend laid up ill at home. If you want to know the <strong>in</strong>gredients of mafongo (a<br />

dish native to Puerto Rico) and the order <strong>in</strong> which they are added, you have<br />

to watch cont<strong>in</strong>uously as someone makes it. (Mak<strong>in</strong>g it yourself, as part of<br />

participant observation, produces embodied knowledge, yet a third k<strong>in</strong>d of<br />

<strong>in</strong>formation.)<br />

Rob<strong>in</strong> O’Brian (1998) comb<strong>in</strong>ed CM and spot sampl<strong>in</strong>g <strong>in</strong> her study of<br />

Mayan craftswomen <strong>in</strong> Chiapas, Mexico. The women sold their crafts to tourists<br />

at a local market. Several times a week, O’Brian went through the market<br />

(enter<strong>in</strong>g from a randomly selected spot each time) and coded what every<br />

woman craft seller was do<strong>in</strong>g, us<strong>in</strong>g a check sheet adapted from Johnson<br />

(1987) standardized time allocation activity codes.<br />

O’Brian also did cont<strong>in</strong>uous monitor<strong>in</strong>g for 3 hours of 15 women, and these<br />

two k<strong>in</strong>ds of data produced more <strong>in</strong>formation than either k<strong>in</strong>d alone. Her<br />

aggregate, spot-sampl<strong>in</strong>g data showed that the women spent 82% of their time<br />

wait<strong>in</strong>g for tourists to buy someth<strong>in</strong>g. The women weren’t just sitt<strong>in</strong>g around,<br />

though. They spent 17% of their wait<strong>in</strong>g time produc<strong>in</strong>g more crafts (do<strong>in</strong>g<br />

macramé or embroidery or hand-sp<strong>in</strong>n<strong>in</strong>g wool) and another 17% eat<strong>in</strong>g,

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