Detecting Climate Delay Discourses in Danish Parliamentary Speeches: A Large Language Model Approach.

As scientific consensus on anthropogenic climate change has solidified, outright denial in political debate has largely given way to more subtle forms of climate change rejection. These so-called climate delay discourses acknowledge the problem yet justify inaction, posing a growing challenge to eff...

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Publicado en:Digital Humanities in the Nordic & Baltic Countries Publications (DHNB Publications) Vol. 8; no. 1; pp. 1 - 21
Autores principales: Küseler, Camilla Buur, Meier, Florian
Formato: Artículo
Publicado: University of Oslo 2026
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Detecting Climate Delay Discourses in Danish Parliamentary Speeches: A Large Language Model Approach.
      aug:
        au:
          Küseler, Camilla Buur
          Meier, Florian
        affil: Department of Culture and Communication, Aalborg University, Copenhagen
      su:
        Political debates
        Climate change
        Polarization (Social sciences)
        Government policy on climate change
        Political oratory
        Climate change mitigation
        Classification algorithms
        Language models
        Denmark
      sug:
        subj:
          Denmark
          Political debates
          Climate change
          Polarization (Social sciences)
          Government policy on climate change
          Political oratory
          Climate change mitigation
          Classification algorithms
          Language models
      keyword:
        climate change
        climate delay discourse
        large language models
        parliamentary speeches
      ab: As scientific consensus on anthropogenic climate change has solidified, outright denial in political debate has largely given way to more subtle forms of climate change rejection. These so-called climate delay discourses acknowledge the problem yet justify inaction, posing a growing challenge to effective climate communication and policymaking. This study operationalises Lamb et al.'s (2020) typology of climate delay discourses to examine 25 years of Danish parliamentary speeches (1998-2022). Using a keyword-based retrieval method, we identified approximately 34,000 climate change-related speech segments and applied large language models (LLMs) to classify them according to delay discourse categories. We compared zero-shot and few-shot prompting strategies, including variations with chain-of-thought reasoning, to evaluate LLM performance on complex rhetorical classification tasks. Few-shot prompting delivered promising results with respect to both recall and accuracy, while chain-of-thought reasoning provided limited benefits and, in some cases, harmed performance. Temporal and partisan analyses reveal that delay discourses have been consistently present in Danish political debate, with a marked increase in recent years. The most prevalent discourse, all talk, little action, reflects the gap between ambitious climate targets and policy implementation, particularly among governing parties. While right-leaning parties often shift responsibility away from Denmark, left-leaning and green parties more frequently invoke appeals to social justice. Our findings demonstrate both the promise and the limitations of LLMs for large-scale political discourse analysis and provide evidence that climate delay discourses are a routine part of Danish parliamentary debates.
      pubtype: Academic Journal
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    language: English
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