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Distinguishing intergroup and long-distance relationships

Author

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  • Pisor, Anne

    (Washington State University)

  • Ross, Cody T.

Abstract

Intergroup and long-distance relationships are both central features of human social life, but because intergroup relationships are emphasized in the literature, long-distance relationships are often overlooked. Here, we make the case that intergroup and long-distance relationships should be studied as distinct, albeit related, features of human sociality. First, we review the functions of both kinds of relationship: while both can be conduits for difficult-to-access resources, intergroup relationships can reduce intergroup conflict while long-distance relationships are especially effective at buffering widespread resource shortfalls. Second, to illustrate the importance of distinguishing the two relationship types, we present a case study from rural Bolivia. Combining ethnography and two different experimental techniques, we find that the importance of intergroup relationships—and the salience of group membership itself—varies across populations and across methods. While ethnography revealed that participants often rely on long-distance relationships for resource access, we were unable to capture participant preferences for these relationships with a forced-choice technique. Taken together, our review and empirical data highlight that: (1) intergroup and long-distance relationships can have different functions and can be more or less important in different contexts, and (2) validating experimental field data with ethnography is crucial for work on human sociality. We close by highlighting future directions for research on long-distance relationships in humans.

Suggested Citation

  • Pisor, Anne & Ross, Cody T., 2021. "Distinguishing intergroup and long-distance relationships," OSF Preprints u8tgq_v1, Center for Open Science.
  • Handle: RePEc:osf:osfxxx:u8tgq_v1
    DOI: 10.31219/osf.io/u8tgq_v1
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    References listed on IDEAS

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    1. Aizaki, Hideo, 2012. "Basic Functions for Supporting an Implementation of Choice Experiments in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 50(c02).
    2. Vithala R. Rao, 2014. "Applied Conjoint Analysis," Springer Books, Springer, edition 127, number 978-3-540-87753-0, March.
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