Wednesday, 11 December 2013

Oswalt’s techno-units

Tool complexity was quantified by the number of ‘techno-units’. A techno-unit was defined by Oswalt (1976, p. 38) as ‘an integrated, physically distinct and unique structural configuration that contributes to the form of a finished artefact’. Techno-unit counts are based on verbal descriptions, illustrations and photographs from the eHRAF and ranged from one techno-unit (e.g. a stick used for prying shellfish from the reef) to 16 techno-units (e.g. an untended crab trap made of a bamboo tube and baited lever); see the electronic supplementary material for an example of techno-unit coding. In contrast to Oswalt, we include decorative elements in the techno-unit counts because the production of any part of the tool may be socially learned, and thus subject to the dynamics of the cultural transmission process upon which both models are based. If a given tool was present in more than one society's tool kit, we coded that tool independently for each society where information was available. Next, we computed the mean of these techno-unit estimates. We then used the mean as the techno-unit estimate for that tool across all societies where it was present, replacing the original independent estimates. This helped to control for potential coder and/or ethnographer bias and worked against our hypotheses by decreasing variation between groups. 

Measuring Lithic Technology Complexity

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We define technological complexity as the minimum amount of information that is needed to manufacture a product. This definition is in line with other formalized definitions of complexity (Shannon and Weaver 1949). Computer scientists, for example, have defined the complexity of an algorithm as the shortest string length, or the smallest number of bits of information, that is necessary to describe it (Chaitin 1970). This information criterion is analogous to the various measures of richness used to describe biological systems that are defined as the number of unique types of some constituent present within an aggregate group. For instance, at the level of the organism, biological complexity has been measured as the count of cell types (Bonner 1988). At the level of an ecosystem, biological complexity has been measured as the count of unique species it contains (Bonner 1988). Finally, the complexity of animal behavior has also been estimated by counting the number of elemental “building blocks” that is associated with a specific behavior or, at a larger scale, as the number of acts in a species’ behavioral repertoire (Sambrook and Whiten 1997; Whiten et al. 1999).
In the same spirit, we argue that the complexity of a technology can be measured by counting the number of elemental building blocks associated with it. We call these building blocks “procedural units.” We define procedural units as mutually exclusive manufacturing steps that make a distinct contribution to the finished form of the product of a technology. Focusing on lithic technology, the count of procedural units present in a tool reduction sequence is a measure of complexity because it reflects the minimum amount of information that is needed to carry it out to a successful end.
This procedural-unit approach to stone-tool complexity parallels Oswalt’s “techno-units” (Oswalt 1976). Oswalt assessed the complexity of food-getting technologies by counting (1) the number of tool types present in a tool kit, which he called “subsistants,” and (2) the number of integrated and physically distinct structures that contribute to the finished form of a tool, which he called “techno-units.” Oswalt’s method is powerful because it allows for the measurement of technological complexity cross-culturally. It has been applied to ethnographic data to test a wide range of hypotheses, including hypotheses about the ecological determinants of technological complexity (Collard, Kemery, and Banks 2005; Collard et al. 2011; Shott 1986; Torrence 1983, 1989, 2000) and the effect of demography on the evolution of technologies (Collard, Kemery, and Banks 2005; Collard et al. 2011; Kline and Boyd 2010; Oswalt 1976).

Measuring the Complexity of Lithic Technology

Charles Perreault, P. Jeffrey Brantingham, Steven L. Kuhn, Sarah Wurz, and Xing Gao

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