At this week’s MCQLL meeting on Tuesday, September 20 15h00 – 16h00, Maximilian Puelma Touzel, research associate at Mila and UdeM, will give a talk titled Ideology as topic-topic correlation structure
inferred from topic models fit to open-ended Responses of Canadians to the Carbon Tax. An abstract of the talk follows.
The meeting will be hybrid in-person and on Zoom. We’ll be meeting in person in room 117 of the McGill Linguistics department at 1085 Dr Penfield. If you’d like to attend virtually, Zoom meetings will be held here.
The success of a given sustainability transition policy depends on what citizens think about it. Carbon pricing is a timely example. Despite the federal government’s estimate that 80% of households
are receiving a cash surplus as a result of this policy, its popularity is evenly split. Previous work shows that public support for taxation is strongly influenced by ideology. We wondered what
deeper insights underlie how identity factors impact ‘carbon tax opposition’, with the hope of informing more effective messaging. To address this question, we use open-ended responses of Canadians
elaborating on their support of or opposition to the tax. Structural topic models incorporate rich metadata and have been used to study carbon tax opinion in other countries. We have fit these models and are beginning to use them to explore how identity factors shape the topics people talk about and their correlation structure. Here, we present a first set of questions and results designed to be agnostic to (ultimately ad hoc) topic labelling. We find topics learned from oppose responses are more coherent and that oppose topic weights are less heterogeneous, lower-dimensional, and more (and more densely) correlated than those inferred from support responses. As a result, dislodging conservative’s opposition to carbon pricing, if possible at all, may require addressing multiple beliefs in tandem to overcome the putatively stabilizing, cooperative effect of the highly correlated topics used to justify that opposition.