SAGE brings the availability of election results for the 2019 Indian Lok Sabha election down from an average of 2 million voters per each of 543 constituencies to 1,000 voters across nearly a million polling stations.

SAGE also enables analyses of previously more democratic elections in several current autocracies. Take, for instance, the 2013 Venezuelan presidential elections, mapped below at the polling station level.

Polling station data from SAGE reveal considerable spatial variation in the 2021 Hong Kong elections, with pro-establishment strongholds spread across the New Territories, mixed support patterns through Kowloon, and pockets of opposition votes concentrated on Hong Kong Island.

If you're interested in seeing any detailed election results from the Small-Area Global Elections (SAGE) archive, let me know in the replies. I'll start with parliamentary elections in Poland in 1991 and 2023.

To receive notification of when SAGE is released alongside the corresponding paper, fill out this form (just email and affiliation): shorturl.at/6JbKv. The full working paper can be found here: www.dropbox.com/scl/fi/f5ol5...

To receive notification of when SAGE is released alongside the corresponding paper, fill out this form (just email and affiliation): shorturl.at/6JbKv. The full working paper can be found here: www.dropbox.com/scl/fi/f5ol5...


I propose several possible mechanisms whereby conditions of discordant composition may or may not arise, and in turn urban-rural polarization: economic structure, sociocultural organization, institutional legacies, and the nature of modernization. (7/8)

To partially explain these findings, I introduce a theory of “discordant composition”: urban–rural cleavages arise when politically salient traits cluster geographically, letting parties tailor local appeals. Without such clustering, the divide is muted. (6/8)

The results reveal considerable cross-national variation. In many countries, urban–rural differences are weak or even ideologically reversed (rural–left, urban–right), and their strength isn’t solely explained by economic development or industrial activity. (5/8)

I merge these 10 billion votes with 2.3 billion building footprints to measure urbanicity via nearest-neighbor distances, an approach that better captures how people perceive urban and rural areas. I validate this against population density using an original survey. (4/8)

Election returns were collected and compiled over the course of 3 years. One example: geocoded election returns for nearly 1 million polling stations in the 2019 Indian general election, where I also matched thousands of OCR’d candidates by hand to their respective parties. (3/8)

In this dataset, which I term the Small-Area Global Elections archive (SAGE), I provide standardized returns matched with artificial or actual spatial boundaries in every democracy and the previous democratic elections of several current autocracies. (2/8)

Urban–rural cleavages are seen as a defining political divide. But does this polarization hold worldwide? My new working paper tests this question using an original dataset of granular, geocoded election returns from 106 countries (polling station-level in 70). (1/8)