Urban segregation is a widespread phenomenon with profound social implications, and one that presents difficult measurement challenges. Segregation indexes may be affected by scale or zoning biases of the modifiable areal unit problem (MAUP). In this article, we develop a methodology that relies on spatial clustering algorithms to simultaneously cope with both kinds of MAUP biases, and we test it with complete census data for most Chilean cities. We find a robust correlation between segregation and city size, contesting previous claims about the spuriousness of this relationship. We also show that socioeconomic polarization is a widespread phenomenon in Chile and that it is not just a problem of disadvantaged groups’ concentration. Based on these results, we suggest that area-based desegregation policies should be generally reinforced, and complemented in big Chilean cities with housing-mix policies. We argue that using spatially unbiased segregation indexes could improve comparative urban studies.