Collaborative Innovation Networks by Francesca Grippa João Leitão Julia Gluesing Ken Riopelle & Peter Gloor

Author:Francesca Grippa, João Leitão, Julia Gluesing, Ken Riopelle & Peter Gloor
Language: eng
Format: epub
Publisher: Springer International Publishing, Cham

3 Methods

John Ziker’s (JPZ) research in the Ust’-Avam community comprised a sum of 36 months from 1994 through 2007. During field trips in 2001 and 2003, Ziker investigated the primary distributions of hunters and their respective households (Ziker et al. 2015), as well as women’s sharing patterns discussed here. Women residing in a household without a hunter (n = 10) were asked to complete a diary (a survey developed specifically for this investigation) by making entries for 7 days, every 3 weeks. Diary responses and the results of interviews and observations JPZ conducted over a 12-week period (August–October 2001) were combined with community census and genealogical data for our analyses. These data included 162 distributions among 69 household dyads. One report from August 2002 and the remainder of the 2003 data were not included in this analysis.

To analyze the independent variables influencing the Ust’-Avam sharing patterns we used matrix regression, specifically the MRQAP (double-Dekker semi-partialling) process in UCINET (Borgatti Everett and Freeman 2002). Genealogies were analyzed in the Descent program (Hagen 2007). The independent variables used in the matrix regressions included: kinship, calculated as the maximum genealogical relatedness between households (r max ), the transpose of the dependent variable matrix representing reciprocal food transfers (reciprocity), ego-to-sharer returned gifts in non-food goods and services (returned gifts), sharer-to-ego visitation frequency (social association), the differences in the number of active individual sharers in sharing households (active sharers differences), and the differences in the number of total household occupants (occupant differences). These variables were used to represent the predictions derived from explanatory hypotheses (Gurven 2004; Ziker and Schnegg 2005). Interhousehold kinship and reciprocal food sharing were relevant to kin selection (Hamilton 1964) and reciprocal altruism (Trivers 1971), respectively. The returned gifts variable was relevant to the costly signaling hypothesis (Zahavi 1975).

We also included the differences in the number of active sharers in each household as a control variable. Obviously, if more than one individual in each household was sharing, the frequency of food shared could be greater than in households with only one sharer. The differences in the total number of household members for each household represented in the sample were used to provide indices of relative need (Blurton Jones 1984). The sharer-to-ego visitation frequency provided an independent measure of social association (following Koster and Leckie 2014). Finally, we checked an additional attribute matrix: the sum of active individual sharers in sharing households. This variable was relevant to the hypothesized risk-buffering function of reciprocal altruism, but it was an insignificant predictor of the food sharing in this sample.

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