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Russel-Research-Method-in-Anthropology

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Direct and Indirect Observation 431<br />

fourth. His data show that garden<strong>in</strong>g takes up about 26% of the Abelam’s<br />

daylight hours, but only 20% of their total wak<strong>in</strong>g time <strong>in</strong> each 24-hour period.<br />

Of course, it may not always be possible to conduct TA studies at night.<br />

Johnson, you’ll remember, made a po<strong>in</strong>t of the fact that the Machiguenga discourage<br />

nighttime visit<strong>in</strong>g. Scaglion, on the other hand, worked among a people<br />

who ‘‘go visit<strong>in</strong>g at unusual hours, even when their prospective host is<br />

likely to be sleep<strong>in</strong>g.’’<br />

Scaglion, <strong>in</strong> fact, rather enjoyed show<strong>in</strong>g up at people’s houses dur<strong>in</strong>g odd<br />

hours <strong>in</strong> 1983. He had done his doctoral research <strong>in</strong> the same village <strong>in</strong> 1974–<br />

1975. In those days, he says, ‘‘I was still quite a novelty. . . . I was frequently<br />

awakened by hear<strong>in</strong>g ‘M<strong>in</strong>oa, m<strong>in</strong>e kwak?’ (‘Hey, you, are you sleep<strong>in</strong>g?’).<br />

This study allowed me to return old favors by visit<strong>in</strong>g people <strong>in</strong> the late night<br />

hours to be sure they were sleep<strong>in</strong>g’’ (ibid.:539). (For more examples of TA<br />

studies, see Bock 2002 and Umezaki et al. 2002.)<br />

Cod<strong>in</strong>g and Record<strong>in</strong>g Time Allocation Data<br />

Sampl<strong>in</strong>g is one of two problems <strong>in</strong> TA research. The other is measurement.<br />

How do we know that when Oboler recorded that someone was ‘‘work<strong>in</strong>g,’’<br />

we would have recorded the same th<strong>in</strong>g? If you were with Johnson when he<br />

recorded that someone was engaged <strong>in</strong> ‘‘hygiene behavior,’’ would you have<br />

agreed with his assessment? Every time? You see the problem.<br />

It gets even more thorny. Suppose you work out a cod<strong>in</strong>g scheme that<br />

everyone agrees with. And suppose you tra<strong>in</strong> other observers to see just what<br />

you see. (Rogoff [1978] achieved a phenomenal 98% <strong>in</strong>terobserver agreement<br />

<strong>in</strong> her study of 9 year olds <strong>in</strong> Guatemala.) Or, if you are do<strong>in</strong>g the research all<br />

by yourself, suppose you are absolutely consistent <strong>in</strong> record<strong>in</strong>g behaviors (i.e.,<br />

you never code someone ly<strong>in</strong>g <strong>in</strong> a hammock as sleep<strong>in</strong>g when they’re just<br />

loung<strong>in</strong>g around awake).<br />

Even if all these reliability problems are taken care of, what about observation<br />

validity? What do you do, for example, when you see people engaged <strong>in</strong><br />

multiple behaviors? A woman might be hold<strong>in</strong>g a baby and stirr<strong>in</strong>g a pot at<br />

the same time. Do you code her as engaged <strong>in</strong> child care or <strong>in</strong> cook<strong>in</strong>g? (Gross<br />

1984:542). If someone saw that you were ly<strong>in</strong>g down read<strong>in</strong>g, and you were<br />

study<strong>in</strong>g for an exam, should they record that you were work<strong>in</strong>g or relax<strong>in</strong>g?<br />

Do you record all behaviors? Do you mark one behavior as primary? This<br />

last question has important implications for data analysis. There are only so<br />

many m<strong>in</strong>utes <strong>in</strong> a day, and the percentage of people’s time that they allocate<br />

to activities has to add up to 100%. If you code multiple activities as equally<br />

important, then there will be more than 100% of the day accounted for. Most<br />

TA researchers use their <strong>in</strong>tuition, based on participant observation, to decide

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