Climate adaptation in public-oriented research communication
Lorenzo Zannini & Niall Curry
Abstract
The notion of adaptation has become central to the development of responses to climate-related risks. However, what climate adaptation means in earnest appears highly variable. As impact driven agenda surrounding climate adaptation appear to be having limited influence on policy and practice, globally, it may be that a lack of clarity surrounding what adaptation processes are is diminishing their reach. Given that academics, researchers, and scientists are driving the development of adaptation processes and practices, we argue that gaining a deeper understanding of their discursive construction of climate adaptation could highlight the social realities that shape adaptation processes. To this end, this paper presents a corpus-assisted transitivity analysis of adaptation processes in The Conversation Australia, offering a culturally situated perspective on climate adaptation. Using keyword analysis, a number of key, significant, and widely dispersed verbs were identified and subjected to a transitivity analysis. Each key verb was found to perform a material action process. Through the investigation of the accompanying actors, goals, and circumstances, three dominant themes emerged. These themes related to mitigation, farming, and leadership and together they underscore a cultural epistemology shaped by localised environmental, social, and economic concerns. Overall, this analysis demonstrates that public-oriented research communication produced by academics can be embedded with ideological perspectives surrounding climate adaptation which in turn offers credence to the need to reflect on the general, perhaps misguided perception of academic discourses as value-free, objective science.
2 citations
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.25 × 0.4 = 0.10 |
| M · momentum | 0.55 × 0.15 = 0.08 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.