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Does Market Integration Buffer Risk, Erode Traditional Sharing Practices and Increase Inequality? A Test among Bolivian Forager-Farmers

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Abstract

Sharing and exchange are common practices for minimizing food insecurity in rural populations. The advent of markets and monetization in egalitarian indigenous populations presents an alternative means of managing risk, with the potential impact of eroding traditional networks. We test whether market involvement buffers several types of risk and reduces traditional sharing behavior among Tsimane Amerindians of the Bolivian Amazon. Results vary based on type of market integration and scale of analysis (household vs. village), consistent with the notion that local culture and ecology shape risk management strategies. Greater wealth and income were unassociated with the reliance on others for food, or on reciprocity, but wealth was associated with a greater proportion of food given to others (i.e., giving intensity) and a greater number of sharing partners (i.e., sharing breadth). Across villages, greater mean income was negatively associated with reciprocity, but economic inequality was positively associated with giving intensity and sharing breadth. Incipient market integration does not necessarily replace traditional buffering strategies but instead can often enhance social capital.

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Notes

  1. Results do not vary when including village-level variables and their interaction with other relevant variables in the same multilevel model.

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Acknowledgments

We thank the Tsimane who participated in this study and Tsimane Health and Life History Project personnel. We also thank Monique Borgerhoff Mulder, Sam Bowles, and the participants of the Santa Fe Institute Workgroup on Dynamics of Inequality in Small-scale Societies for stimulating discussions.

Compliance with Ethical Standards

The study and all methods were approved by the Institutional Review Boards (IRB) of the University of California, Santa Barbara, and the University of New Mexico. In Bolivia, all procedures were approved by the Tsimane Government (Gran Consejo Tsimane), by village leaders and by study participants. Because many Tsimane do not read or write, participant permission was verbal and it was obtained twice: an initial affirmation to participate and a second confirmation once all procedures had been explained.

Conflict of Interest

The authors declare no conflicts of interest.

Funding

Funding was provided by grants from the National Science Foundation (BCS-0136274, BCS-0422690) and National Institutes of Health/National Institute on Aging (R01AG024119, R56AG02411). Adrian Jaeggi was supported by postdoctoral fellowships from the Swiss NSF (PBZHP3-133443) and the SAGE Center for the Study of the Mind.

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Correspondence to Michael Gurven.

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Table S1

Summary of sources used to obtain sharing and economic data. (DOCX 12 kb)

Table S2

Descriptive statistics on material and relational wealth variables for the sample of 119 households and nine communities for which data on all variables were available. Gini coefficients are age-adjusted and all monetary values are standardized to 2010 Bolivian currency (Bolivianos, Bs). (DOCX 11 kb)

Table S3

Linear regression models predicting variance in daily food production [CV kcals] by household as a function of material wealth and controls (age, age*age, average date of income interviews, average month of production interviews, number of risk days for production; details for controls not shown). Reported are the best-fit models based on stepwise AIC selection (DOCX 12 kb)

Table S4

Sharing depth and giving intensity as absolute calories rather than proportions. Poisson GLMs and linear regression models showing association between material wealth and giving, receiving, and net giving (giving-receiving) of food controlling for age, age2, and date of wealth interview (details for controls not shown). Best-fit models based on stepwise AIC selection are reported (DOCX 13 kb)

Table S5

Correlations between village-level predictors, and variance inflation factors (DOCX 12 kb)

Table S6

Multilevel Poisson model estimating contingency in food transfers, i.e. the association between giving and receiving at the household and village level. The variances of the contingency measures (in italics) are 10 times higher at the village level (0.01) compared to the household level (0.001) (DOCX 11 kb)

Figure S1

Mean daily food production as a function of household produce income. Solid line is predicted fit and dashed lines are 95 % CI controlling for wealth and average date of production interview. For detailed results see Table 1. (DOCX 50 kb)

Figure S2

Variance (coefficient of variation, CV) in daily food production as a function of wage income, holding the other factor at population average. Solid lines are predicted curves from the best-fit regression model, which included wage labor and wealth, and dashed lines are 95 % CI on these estimates. For detailed results see Table S3. (DOCX 47 kb)

Figure S3

Sharing breadth increases with wealth a) only for those with minimal or no Spanish speaking ability, b) for those with the highest education. For detailed results see Table 4b. (DOCX 86 kb)

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Gurven, M., Jaeggi, A.V., von Rueden, C. et al. Does Market Integration Buffer Risk, Erode Traditional Sharing Practices and Increase Inequality? A Test among Bolivian Forager-Farmers. Hum Ecol 43, 515–530 (2015). https://doi.org/10.1007/s10745-015-9764-y

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