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We classify and analyze >1 million parliamentary speeches related to immigration from 9 national parliaments over several decades in Europe and the United States to track and compare the development of the immigration debate among legislators. To do so, we combine expert annotations, multilingual classifiers, and large-language models. Our approach allows us to analyze the salience of and stance on immigration by parties over time, but also the particular topical emphasis as well as the framing and language used in immigration debates. The resulting dataset enables us to answer key questions, such as whether centrist parties adopt more negative immigration positions once a far-right party enters parliament; whether the US Republican Party more closely resembles European far-right than center-right parties; and how processes of normalization and polarization play out in political speech over time.