Building Quantitative Cross-Cultural Databases From Ethnographic Records: Promise, Problems and Principles

Joseph Watts*, Joshua Conrad Jackson, Chris Arnison, Elise M. Hamerslag, John H. Shaver, Benjamin Grant Purzycki

*Corresponding author for this work

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

2 Citations (Scopus)

Abstract

Quantitative cross-cultural databases can help uncover structure and diversity across human populations. These databases have been constructed using a variety of methodologies and have been instrumental for building and testing theories in the social sciences. The processes and assumptions behind the construction of cross-cultural databases are not always openly discussed by creators or fully appreciated by their users. Here, we scrutinize the processes used to generate quantitative cross-cultural databases, from the point of ethnographic fieldwork to the processing of quantitative cross-cultural data. We outline challenges that arise at each stage of this process and discuss the strengths and limitations of how existing databases have handled these challenges. We suggest a host of best practices for cross-cultural database construction, and stress the importance of coding source meta-data and using this meta-data to identify and adjust for source biases. This paper explicitly discusses the processes, problems, and principles behind cross-cultural database construction, and ultimately seeks to promote rigorous cross-cultural comparative research.

Original languageEnglish
JournalCross-Cultural Research
Volume56
Issue1
Pages (from-to)62-94
Number of pages33
ISSN1069-3971
DOIs
Publication statusPublished - Feb 2022

Keywords

  • bias
  • comparative methods
  • cross-cultural
  • ethnographic records
  • uncertainty
  • variation

Fingerprint

Dive into the research topics of 'Building Quantitative Cross-Cultural Databases From Ethnographic Records: Promise, Problems and Principles'. Together they form a unique fingerprint.

Cite this