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This paper explores the relationship between speaker normalization and dialectal identity in sociolinguistic data, examining a database of vowel formants collected from 88 monolingual American English speakers in Michigan's Upper Peninsula. Audio recordings of Finnish- and Italian-heritage American English speakers reading a passage and a word list were normalized using two normalization procedures. These algorithms are based on different concepts of normalization: Lobanov, which models normalization as based on experience with individual talkers, and Labov ANAE, which models normalization as based on experience with scale-factors inherent in acoustic resonators of all kinds. The two procedures yielded different results; while the Labov ANAE method reveals a cluster shifting of low and back vowels that correlated with heritage, the Lobanov procedure seems to eliminate this sociolinguistic variation. The difference between the two procedures lies in how they treat relations between formant changes, suggesting that dimensions of variation in the vowel space may be treated differently by different normalization procedures, raising the question of how anatomical variation and dialectal variation interact in the real world. The structure of the sociolinguistic effects found with the Labov ANAE normalized data, but not in the Lobanov normalized data, suggest that the Lobanov normalization does over-normalize formant measures and remove sociolinguistically relevant information.