The central topic of this paper is the university in relation to sustainability. The paper discusses the results of a discourse analysis of the way the university is understood in relation to sustainability in academic literature. This is done through combining discourse theory with the data-mining tool topic modelling.

Universities and higher education are often regarded as a crucial actor in society’s strive towards sustainable development. In the remarkably growing literature on the university – sustainability nexus (Hallinger & Chatpinyakoop, 2019), it is said that higher education has an unavoidable responsibility to address sustainability challenges (Gale, Davison, Wood, Williams, & Towle, 2015) and would even be “morally culpable if it did not do everything in its power to address these [sustainability] challenges” (McCowan, 2018, p. 286).

While there seems to be somewhat of an academic consensus about the importance of universities engaging with sustainability, the purposes for doing this are less unambiguous. To give just a few examples: catalyzing and accelerating a societal transition (Stephens & Graham, 2010), reducing campus’ climate-altering emissions (Rappaport & Creighton, 2007), reducing energy costs (Horhota, Asman, Stratton, & Halfacre, 2014), constructing an institutional identity which helps to find a niche to attract the best students (Bardaglio & Putman, 2009), or convincing students to change their carbon emitting behavior (Rappaport & Creighton, 2007).

These examples imply different understandings of what a university actually is or should be (cf. Barnett’s ontological and imaginative domain of the university (2022)). However, in the abovementioned academic field these understandings are all too often implicit and undertheorized (as e.g. pointed towards by Figueiró and Raufflet (2015) and Shephard, Rieckmann, and Barth (2019)). In order to advance our understanding of, and the debate about the university’s role in relation to sustainable development, it is of great importance to first understand how the university appears in the current academic literature about the ‘university – sustainability’ nexus.

This is where the contribution of this paper lies. Its aim is to advance this debate by ‘identifying’ discourses on the university in relation to sustainability in the scientific literature. These discourses will be based on how the university is articulated in relation to sustainability in academic publications. The aim is not to summarize or synthesize the field, but to lay differences and similarities bare, make the different understandings of and approaches to the university more open and sharper, and adding to the vocabulary to foster further debate. In this light, the presented study can be regarded as a configurative review, because the focus lies on the range and nature of concepts (Gough & Thomas, 2016).

This study starts off from a discourse theoretical perspective, more specifically Laclau and Mouffe’s post-structural strand, as originally introduced in Hegemony and socialist strategy (1985), and focuses on how the university is discursively constructed in academic literature on the university & sustainability nexus. Concretely, research that focuses on this nexus is approached as a specific social system (cf. Howarth & Stavrakakis, 2000) that can be characterized by one or several discourses on what a university precisely is or should be. These discourses are continually reproduced and/or challenged by articulatory practices. Scientific publications can be seen as such articulations. The study focuses on how the university is articulated. This is made possible by a combination of this discourse theoretical perspective with the data mining technique topic modelling.

The object of study is the body of academic literature on the university and sustainability. The methodology of the paper is constructed around systematic literature review approaches, the discourse theoretical framework and topic modelling as data-mining technique (as argued for by Jacobs and Tschotschel (2019)). Although the different steps are presented below sequentially for communication reasons, it cannot be emphasized enough that, in practice, this entails an iterative process of pre-processing, topic modelling and analysis of the topic model. Data collection and pre-processing. Through a search query in the research database SCOPUS, 4585 academic publications that deal with the university and sustainability were manually downloaded and prepared for topic modelling (OCRed, converted, cleaned, split, stopwords removed, and lemmatized). Topic modelling. Topic modelling (TM) is an automated content analysis method that allows to analyze large corpora (Arora et al., 2018) by deriving meaning from documents. It is a text mining technique that allows to reduce the complexity of a corpus through finding topics: collections of words that have a high probability of co-occurrence in documents in the corpus (Jaworska & Nanda, 2018). This results in a topic model: a list of topics (with every topic consisting of a list of the most important words in that topic) that represents the corpus. For this study, a topic model consisting of 250 topics was run. Analysis of the topic model. The topic model gives a representation of the ‘aboutness’ of the corpus, but is not the end point of this study. The analysis of the topic model has three main steps. First, the topics are labeled and analyzed to find recurring themes throughout the topics. In a second step, using a list of sensitizing concepts based on the frameworks on sustainable higher education institutions by Filho (2018) and Lozano et al. (2015) a second level of analysis is done to find clusters in the topic model. These sensitizing concepts (Blumer, 1954) offer a “general sense of reference and guidance in approaching empirical instances” (p. 7) and point at what to look for and where to look (Carpentier & Cleen, 2007) without determining what to see. In a third step, building on the discourse theoretical framework, similarities and differences (cf. Östman, 1996) are discerned within the topic model the clusters in order to identify different coherent discourses on the university in relation to sustainability.

The contributions of the paper are twofold. First, the discourse analysis identifies three discourses on the sustainable university: "the sustainable higher education institution", "the engaged community", and "the green tech campus". In this way, it shows how the university appears (or is discursively constructed) in different ways in the corpus, focusing on different areas of the university (i.e. education, campus infrastructure, research, institutional framework, on-campus experience, and outreach & collaboration) in a variety of ways. Every discourse is structured as a net of connected nodes (words or phrases) and is characterized by specific nodal points (the major ideas around which a discourse is constructed). Such a representation of the discourses on the university allows to lay bare similarities and differences and, in a next step, open up a debate about how the university is commonly approached in the corpus and what might be underrepresented or even missing. This contribution allows to further advance the field. Second, the paper also offers a methodological contribution. The combination of discourse theory with topic modelling is novel to the field of environmental and sustainability research and opens up for new ways of analysing large bodies of textual material. While it a is time-consuming and theoretically and methodologically challenging approach, the topic modelling – discourse analysis combination holds many promises for future analyses of, for example, policy documents, university websites, university curricula, textbooks and so on.

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