Types of Intolerance in Elites’ Political Rhetoric: A Proof of Concept for Studying the Targeting of Minorities in Belgium and the U.S.

Over the past fifteen years, Western democracies have witnessed the unfolding of several mediatized episodes of prejudice and violence targeting minorities – migrants dying at Europe’s borders, shootings in LGBTQIA+ venues, family separation policies of migrants in the United States, and forced evictions of Roma communities in France. These events have unfolded alongside a broader political climate increasingly structured by fear, scapegoating, and moralized hostility toward these outgroup minorities. Existing scholarship often links this evolution to elites’ polarizing rhetoric, yet current approaches tend to treat intolerance as a unitary phenomenon and insufficiently distinguish between its qualitatively different discursive forms. This article argues that intolerant rhetoric comprises distinct “shades” that plausibly trigger different reactions among ingroups and outgroups and may vary across political contexts and minority targets. We propose a new conceptual framework that differentiates four mechanisms – (1) moral hierarchization, (2) dehumanization, (3) demonization, and (4) morality shifting – through which political elites construct group-based moral hierarchies and legitimate exclusion or harm. Building on interdisciplinary scholarship on group appeals, moral emotions, and political intolerance, we theorize how these mechanisms range from subtle dual-audience “dog whistles” to explicit discourses that normalize punitive or violent responses toward minorities. To establish proof-of-concept, we analyze elites’ political communication about migrants and LGBTQIA+ communities on Twitter/X in two “most different” cases: Belgium (multiparty coalition-based politics in relatively stable democracy) and the United States (bipartisan and highly polarized politics with evidence of democratic erosion). Empirically, we present the first results of manually coded subsets – 1,512 Belgian tweets (2023–2025) and 1,250 U.S. congressional tweets (2017–2023) – that will be used to develop supervised NLP classification trained on the wider set of data. Our exploratory results demonstrate the feasibility of reliably identifying distinct shades of intolerance in elites’ social media discourse and suggest systematic variation across targets and contexts. The article concludes by outlining a research agenda for longitudinal and cross-national tests of how these discursive mechanisms relate to broader patterns of polarization, discrimination, and the normalization of hostility toward minorities.