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Global, Regional, and Local Network Autocorrelation in the Standard Cross-Cultural Sample

Global, Regional, and Local Network Autocorrelation in the Standard Cross-Cultural Sample There is now considerable evidence in the cross-cultural literature that cultural networks need not be based strictly on spatial propinquity but may develop along other dimensions such as common language, religion, and levels of cultural complexity. In this article, the authors generate networks based on sociocultural distance metrics for these three network dimensions in addition to the usual geographical distance measure and a measure of overall ecological niche similarity. The authors report overall levels of autocorrelation for all five networks using 1,156 Standard Cross-Cultural Sample (SCCS) variables at the global level and for a subset of 422 variables within four regions. The extent to which cultural trait distributions appear to be influenced by combinations of network processes also are assessed. Results from an analysis based on a local autocorrelation statistic provide confirmation of the regional levels of autocorrelation within the SCCS data set. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Cross-Cultural Research: The Journal of Comparative Social Science SAGE

Global, Regional, and Local Network Autocorrelation in the Standard Cross-Cultural Sample

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References (27)

Publisher
SAGE
Copyright
Copyright © by SAGE Publications
ISSN
1069-3971
eISSN
1552-3578
DOI
10.1177/1069397107311186
Publisher site
See Article on Publisher Site

Abstract

There is now considerable evidence in the cross-cultural literature that cultural networks need not be based strictly on spatial propinquity but may develop along other dimensions such as common language, religion, and levels of cultural complexity. In this article, the authors generate networks based on sociocultural distance metrics for these three network dimensions in addition to the usual geographical distance measure and a measure of overall ecological niche similarity. The authors report overall levels of autocorrelation for all five networks using 1,156 Standard Cross-Cultural Sample (SCCS) variables at the global level and for a subset of 422 variables within four regions. The extent to which cultural trait distributions appear to be influenced by combinations of network processes also are assessed. Results from an analysis based on a local autocorrelation statistic provide confirmation of the regional levels of autocorrelation within the SCCS data set.

Journal

Cross-Cultural Research: The Journal of Comparative Social ScienceSAGE

Published: May 1, 2008

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