Defaulting to Inclusion: Producing Sample Datasets for the Global Data Science Classroom
<p dir="ltr">“U.S. defaultism”—the assumption that American contexts, units, and perspectives are universal—manifests in many ways in political science. In this article, I describe how toy datasets commonly employed in quantitative methods courses exemplify this problem. Using custom...
محفوظ في:
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| منشور في: |
2025
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| الملخص: | <p dir="ltr">“U.S. defaultism”—the assumption that American contexts, units, and perspectives are universal—manifests in many ways in political science. In this article, I describe how toy datasets commonly employed in quantitative methods courses exemplify this problem. Using customary units, for instance, is unsuitable for an internationalized higher education system. To address these limitations, I introduce the Qatar Cars (qcars) dataset, a freely available alternative toy dataset that uses International System (SI) units, reflects current global automotive market trends (such as the rise of Chinese manufacturers and electric vehicles), and avoids ethnocentric classifications such as labeling the non-U.S. world “foreign.” Created through collaborative data collection with students, the Qatar Cars dataset maintains the pedagogical advantages of earlier datasets, improves statistical instruction by removing barriers for international audiences, and provides opportunities to discuss data-generating processes and research ethics.</p><h2 dir="ltr">Other Information</h2><p dir="ltr">Published in: Journal of Political Science Education<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1080/15512169.2025.2572320" target="_blank">https://dx.doi.org/10.1080/15512169.2025.2572320</a></p> |
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