| Climate change has become a key topic of concern for countries around the world,and there have been numerous related reports and discourses.Corresponding research has been conducted for years,such as studies on the environment and climate change discourse.However,the research based on the theory of Proximization is still not sufficient.Therefore,this study selects the theory of Proximization as a tool to analyze media reports on climate change as the corpus,in order to explore how this process is accomplished.From the perspective of Cap’s Proximization theory,this paper analyzes the news about climate change that was published by the Washington Post.This paper chooses the news published during the 26 th United Nations Climate Change Conference(November1-12,2021),in order to reveal what strategies the speakers use systematically,so as to achieve the purpose of legalization.The result shows that,in the spatial dimension,writers use noun phrases to portray climate change-related threats as a real threat and use various verb phrases to indicate how the threat is approaching people.In the temporal dimension,the writers tend to use the past tense and present perfect tense to contrast the increasingly severe nature of climate change and the trend of increasing disasters.In terms of the value dimension,the writers use noun phrases with positive noun phrases to attribute positive values to energysaving and carbon reduction actions that are beneficial for alleviating climate change and saving the earth and humanity while using noun phrases with negative connotations to condemn behaviors that are not conducive to energy-saving and carbon reduction,such as the use of traditional fossil fuels,which exacerbates climate change and harms the overall interests of humanity.This study enriches the research perspective of legalization process in climate discourse in news media.It is conducive to expanding the research breadth and depth of Proximization theory,and it also plays a referential role for related research to a certain extent. |