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Russel-Research-Method-in-Anthropology

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Introduction to Qualitative and Quantitative Analysis 453<br />

ultimately all qualitative. It starts before you collect data—you have to have<br />

some ideas about what you’re go<strong>in</strong>g to study—and it cont<strong>in</strong>ues throughout<br />

any research effort. As you develop ideas, you test them aga<strong>in</strong>st your observations:<br />

Your observations may then modify your ideas, which then need to be<br />

tested aga<strong>in</strong>, and so on. Don’t look for closure <strong>in</strong> the process. If you’re do<strong>in</strong>g<br />

it right, it never stops.<br />

Most methods for quantitative analysis—th<strong>in</strong>gs like factor analysis, cluster<br />

analysis, regression analysis, and so on—are really methods for data process<strong>in</strong>g<br />

and for f<strong>in</strong>d<strong>in</strong>g patterns <strong>in</strong> data. Interpret<strong>in</strong>g those patterns is up to you.<br />

Interpretation—tell<strong>in</strong>g us what f<strong>in</strong>d<strong>in</strong>gs mean, l<strong>in</strong>k<strong>in</strong>g your f<strong>in</strong>d<strong>in</strong>gs to the<br />

f<strong>in</strong>d<strong>in</strong>gs of other research—starts with ideas <strong>in</strong> your head and comes out <strong>in</strong><br />

words on paper. It’s a pretty qualitative exercise.<br />

Don’t worry about gett<strong>in</strong>g ideas. Once you have data <strong>in</strong> your hands, words<br />

or numbers, your hardest job will be to sort through all the ideas you get and<br />

decide which ones to test. And don’t worry about see<strong>in</strong>g patterns <strong>in</strong> your data<br />

or about not be<strong>in</strong>g able to come up with causal explanations for th<strong>in</strong>gs you<br />

see. It can happen very fast, often <strong>in</strong> a matter of hours or days after start<strong>in</strong>g<br />

any research project, so be suspicious of your pet ideas and cont<strong>in</strong>ually check<br />

yourself to make sure you’re not <strong>in</strong>vent<strong>in</strong>g or at least not embellish<strong>in</strong>g patterns.<br />

See<strong>in</strong>g patterns that aren’t there happens all the time <strong>in</strong> research, qualitative<br />

or quantitative, just from eagerness and observer expectations. If you are<br />

highly self-critical, your tendency to see patterns everywhere will dim<strong>in</strong>ish as<br />

the research progresses.<br />

The Constant Validity Check<br />

The problem can also get worse, though, if you accept uncritically the folk<br />

analyses of articulate or prestigious <strong>in</strong>formants. It’s important to seek the emic<br />

perspective and to document folk analyses (Lofland 1971), but as your <strong>in</strong>terviews<br />

and field notes pile up, try consciously to switch back and forth between<br />

the emic and etic perspectives. Check yourself from either buy<strong>in</strong>g <strong>in</strong>to folk<br />

explanations or reject<strong>in</strong>g them without consider<strong>in</strong>g their possible validity. It’s<br />

not hard to do this, it’s just hard to remember to do it systematically. Here are<br />

some guidel<strong>in</strong>es.<br />

1. If you are <strong>in</strong>terview<strong>in</strong>g people, look for consistencies and <strong>in</strong>consistencies among<br />

knowledgeable <strong>in</strong>formants and f<strong>in</strong>d out why those <strong>in</strong>formants disagree about<br />

important th<strong>in</strong>gs.<br />

2. Whenever possible, check people’s reports of behavior or of environmental conditions<br />

aga<strong>in</strong>st more objective evidence. If you were a journalist and submitted a<br />

story based on <strong>in</strong>formants’ reports without check<strong>in</strong>g the facts, you’d never get it

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