This special issue aims to explore the semantic and pragmatic dimensions of meaning in terms of their significance and relevance in the study of argumentation. Accordingly, the contributors to the project, who have all presented their work during the 2nd Argumentation and Language conference, which took place in Lugano in February 2018,1 have been specifically instructed to produce papers which explicitly tackle the importance of the study of meaning for that of argumentative practices. All papers therefore cover at least one (...) aspect of this complex relationship between argumentation and meaning, which contributes to delivering a state-of-the-art panorama on the issue. Drawing from computational linguistics, semantics, pragmatics and discourse analysis, the contributions to this special issue will illuminate how the study of meaning in its different forms may provide valuable insights for the study of people’s argumentative practices in different contexts, ranging from the political to the private sphere. This introductory discussion tackles specific aspects of the intricate relationship between pragmatic inference and argumentative inference – that is, between meaning and argumentation –, provides a brief survey of existing interfaces between the study of meaning and that of argumentation, and concludes with a presentation of the contributions to this special issue. (shrink)

This article offers a first large scale analysis of argumentative polylogues in the fracking controversy. It provides an empirical methodology that identifies, from large quantities of text data through semantic frame analysis, the many players, positions and places presumed relevant to argumentation in a controversy. It goes beyond the usual study of framing in communication research because it considers that a controversy’s communicative context is shaped, and in turn conditions, the making and defending of standpoints. To achieve these novels aims, (...) theoretical insights from frame semantics, knowledge driven argument mining, and argumentative polylogues are combined. The macroscope is implemented using the Semafor parser to retrieve all the semantic frames present in a large corpus about fracking and then observing the distribution of those frames that semantically presuppose argumentative features of polylogue. The prominent indicators are Taking_sides, Evidence and Reasoning. The automatic retrieval of the words associated with the core elements of the semantic frame enables the mapping of how different players, positions, and discussion venues are assembled around what is treated as disagreeable in the controversy. This knowledge driven approach to argument mining reveals prototypical traits of polylogues related to environmental issues. Moreover, it addresses a problem in conventional frame analysis common in environmental communication that focuses on the way individual arguments are presented without effective consideration of the argumentative relevance the semantics and pragmatics of certain frames operating across discourses. (shrink)

Energy democracy hopes to foster community engagement and participation in shaping our transition from fossil fuels to a renewable energy-based economy. These considerations result from critiques by environmental justice, climate justice, and just transition advocates. Although many are sympathetic to energy democracy ideals, climate goals often are articulated in math terms. This essay defines the aforementioned key terms and asks: what are the limitations and possibilities of engaging publics when climate action solely is articulated in numbers? A compelling case study (...) is the City of Boulder – recognized as a global leader in climate science and a national leader in innovative environmental planning. This essay shares work from 2016, when the City shared a climate action plan for public feedback, supported several public participation events, and passed climate action legislation goals. We argue a just transition and energy democracy ideals are hindered if we reduce climate goals to math. (shrink)