In the context of socio-technical transitions, a research stream has emerged around notions like destabilisation, decline, phase-out, discontinuation, collapse, dismantling, rolling back, failure, ends of, losses etc. The existence of so many ways out of established socio-technical regimes has been capturing attention within transitions studies (Rosenbloom and Rinscheid 2020), and in the world-at-large as means for addressing systemic environmental issues (Rinscheid et al 2022). This is an exciting prospect, signalling an increasing focus on processes by which undesirable system lock-ins may be overturned, and bringing new questions to bear on transition challenges, such as issues of power and incumbencies (Stirling 2019). The wealth of such enquiries is evidenced by the multiplicity of conceptual entry points (Turnheim 2022) and the multiplication of empirical research. Nonetheless, framings of the destabilisation problem remain rather homogenous within transitions studies, and this is likely true of other fields of importance to civil society, policy, management and decision-making. Our hypothesis is then that destabilisation exists as a research problem for various strands of social sciences, independently of the constitution of our epistemic community of transitions studies (and very likely preceding it). Following Andy Stirling’s injunction to Open up! and Pluralise!, this paper focuses on exploring the (expected) breadth of research concerned with destabilisation problems within the social sciences, in search for a variety of problem formulations, problem structures, concepts, methods and empirical sites – all of which may be put to work to mutually enrich those perspectives. Measuring and qualifying the scope and diversity of destabilisation research outside transition studies leads to the challenge of positively accounting for this plurality of perspectives in our work, as well as establishing the relevance and impacts of studies on these phenomenons on areas of policy and decision making. To do this, our approach focuses on the exploration of bibliographic data – up to tens of thousands of documents – which we identify, extract, explore and analyse using a mixed methods approach, building on synergies between quantitative and qualitative work. For that we employ text analysis, grow a corpus by searching for its lexical neighbours, perform thematic multi-level clustering of documents with domain-topic modelling (Hannud Abdo, 2021), and carry out sense-making through the study of network representations and the systematic coding and annotation of documents by domain experts.