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KINSHIP AND OTHER DOMAINS

This concern for understanding cultural differences in how people cut the natural world goes a long way back in anthropology—all the way to the early interest in kinship. Lewis Henry Morgan (1997 [1870]) studied systems of kinship nomenclature. His work made clear that if someone says, ‘‘This is my sister,’’ you can’t assume that they have the same mother and father. Lots of different people can be called ‘‘sister,’’ depending on the kinship system. And in his work with the Murray Islanders (in the Torres Straits between Australia and Papua New Guinea) and then later with the Todas of southern India, W.H.R. Rivers developed the genealogical method—those ego-centered graphs for organizing kinship data that we take for granted today—as a way to elicit accurately and systematically the inventory of kin terms in a language (Rivers 1910, 1968 [1914]).

Anthropologists also noticed very early that, although kinship systems could be unique to each culture—which would mean that each system required a separate set of rules— they simply weren’t. Alfred Kroeber showed in 1909 that just eight features were needed to distinguish kinship terms in any system: (1) whether the speaker and the kin referred to were of the same or different generations; (2) the relative age people who are of the same generation—older or younger brother, for example; (3) whether the person referred to is a collateral or a lineal relative; (4) whether the person referred to is an affinal or consanguineal relative; (5) whether the relative is male or female; (6) whether the speaker is male or female; (7) whether the person who links the speaker and the relative is male or female; and (8) whether the person who links the speaker and the relative is alive or dead.

Now, if you first choose whether to use or not use any of those eight features and then choose among the two alternatives to each feature, you can concoct 38 = 6,561 kinds of kinship systems. But, although there are some rare exceptions (the bilineal Yako of Nigeria, the ambilineal Gilbert Islanders), most of the world’s kinship systems are of one those familiar types you studied in Anthropology 101—the Hawaiian, Sudanese, Omaha, Eskimo, Crow, and Iroquois types. Early anthropologists found it pretty interesting that the world’s real kinship systems comprised just a tiny set of the possibilities, and to this day, a small, hardy band of anthropologists continues to study the elements of these systems and how those elements are associated with particular political, economic, or environmental conditions (Kronenfeld 2009; White and Schweizer 1998) (Further Reading: kinship studies).

An interest in classifying kinship systems led to methods for discovering sets of terms in other domains, like kinds of foods, things to do on the weekend, kinds of crime, bad names for ethnic groups, dirty words, names for illnesses, etc. Note that none of these is about people’s preferences. If we ask people which of two political candidates they favor in an election, we might also ask them about their income, their ethnicity, their age, and so on. Then we look for packages of variables about the people that predict their preference for a candidate. In cultural domain analysis, we’re interested in the items that comprise the domain—the illnesses, the edible plants, the jobs that women and men do, etc.—and how those items are related to each other in people’s minds (Borgatti 1999; Spradley 1979) (box 10.1). (More about building folk taxonomies in chapter 17.)

The methods for collecting data about the content and structure of cultural domains include free lists, sentence frames, triad tests, pile sorts, and paired comparisons. All of these methods produce a lot of data very quickly and some of them (particularly free lists and pile sorts) are even fun for people to do. And, with software, like ANTHROPAC (Borgatti 1992a) and UCINET (Borgatti et al. 2002), it’s easy to analyze these data. We’ll return to analyzing these kinds of data in chapter 16 (Further Reading: data collection for domain analysis).

 
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