Decarbonising energy regimes: methodological explorations and empirical insights for policy

Research output: ThesisDoctoral ThesisCollection of Articles

Abstract

Decarbonisation is an urgent, global challenge now widely recognised by policymakers, researchers, businesses and citizens alike. While decarbonisation presents a systemic challenge to our societies, it is increasingly framed as a political challenge. Shifting towards a fossil free future is a value-laden process, prone to political contestation. It is thus critical to examine politics and policy processes that influence and condition energy system change.

This dissertation advances research on decarbonisation policy and politics by exploring methodological questions that help improve synergies between policy studies and energy transition studies. It sets out to answer the following research question: What novel contributions can textual methodologies bring to the study of decarbonisation policy and politics, both in terms of methods and empirical insights? The dissertation takes an interest in discursive approaches and unsupervised machine learning methods, in particular that of topic modelling, while having decarbonisation as the empirical context.

The methodological exploration is carried out on two levels. First, the potential and limitations of each group of method are studied on the meta-level. Second, each method is applied to an empirical case. A topic modelling analysis is conducted on the development of the European Energy Union project, while the decline of coal-fired power generation in the United Kingdom is examined through a discourse analysis.

The findings indicate that discursive methodologies can enhance our understanding of the role of political ideology and state orientation, publics, institutional and policy change in decarbonisation processes. In addition, discursive approaches are found to complement the classical energy transition frameworks. The examination of topic modelling shows that while the method can be used to examine policy-relevant corpora with an unprecedented scale and scope, seeking to gain straightforward qualitative or policy relevant value from the topic modelling output risks being misleading.

As a novel methodological contribution, this dissertation suggests that topic modelling brings added value to textual analysis when used in mixed-method designs. To exemplify this, the study proposes embedded and sequential designs for incorporating topic modelling into the analytical processes of different qualitative textual methods. Taken together, the findings encourage scholars to further experiment with the use of computer mediated textual analysis approaches in practice.

This study also highlights several higher level implications for research and policy. It calls for in-depth methodological dialogue among computational scientists, statistical experts and social scientists. This is because developing computational social science approaches requires that the models are designed to match the real-world societal phenomena they are applied to. Furthermore, the results provide important lessons learnt for transition scholars and policy-makers. The UK case shows that coal declined rapidly and with relatively little resistance by incumbent actors. The results also reveal how the Energy Union’s policy priorities have been increasingly geared towards decarbonisation objectives by furthering policy convergence between climate-security and energy efficiency-affordability paradigms.
Original languageEnglish
Awarding Institution
  • University of Helsinki
Supervisors/Advisors
  • Hukkinen, Janne, Supervisor
  • Janasik, Nina, Supervisor
  • Toikka, Arho, Supervisor
Award date10 Mar 2020
Place of PublicationHelsinki
Publisher
Print ISBNs978-951-51-3425-7
Electronic ISBNs978-951-51-3426-4
Publication statusPublished - 21 Feb 2020
MoE publication typeG5 Doctoral dissertation (article)

Fields of Science

  • 5142 Social policy

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