 The coexistence of heterogeneous representations (including theories, models, and explanations) is ubiquitous in scientific practice. Different branches of science offer different theories and laws, raising questions about the nature of the (e.g., reductive and non-reductive) relationships between them. Within a discipline, heterogeneous models or explanations of the same phenomenon may also co-exist. Such cases of representational plurality are now well-documented in various scientific fields. In nuclear physics, for example, several models of an atomic nucleus are available and the same goes for fluid mechanics, which offers various types of modelisation of turbulent flows (Morrison 2011); in economics, a multiplicity of models exist side by side as a base for policy decisions (Rodrik 2015); in climate science, the use of multiple simulation models is a common strategy (Parker 2006; Edwards 2010); behavioral biology offers many examples of co-existence of multiple explanations (Mitchell 2003; Longino 2013; Muszynski &amp; Malaterre 2020). Various pluralist frameworks have been developed to address such cases of plurality, which amount to different views both on the raison d’être of these situations and on the appropriate epistemic attitudes towards them.