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This paper examines the construction and use of data sets in political science. We focus on three interrelated questions: How might we assess data quality? What factors shape data quality? and How can these factors be addressed to improve data quality? We first outline some problems with existing data set quality, including issues of validity, coverage, and accuracy, and we discuss some ways of identifying problems as well as some consequences of data quality problems. The core of the paper addresses the second question by analyzing the incentives and capabilities facing four key actors in a data supply chain: respondents, data collection agencies (including state bureaucracies and private organizations), international organizations, and finally, academic scholars. We conclude by making some suggestions for improving the use and construction of data sets. It is a capital mistake, Watson, to theorise before you have all the evidence. It biases the judgment. —Sherlock Holmes in “A Study in Scarlet” Statistics make officials, and officials make statistics.” —Chinese proverb
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Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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