Thursday, March 7, 2024 2:30pm to 3:20pm
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1111 Engineering Drive, Boulder, CO 80309
Kath Landgren, Cooperative Institute for Research in Environmental Science (CIRES), University of Colorado Boulder
Modeling misperception of public support for climate policy
Mitigating the consequences of climate change and reducing political polarization are two of the biggest problems facing society today. These problems are intertwined, since meeting international climate-mitigation targets requires implementing policies that accelerate the rate of decarbonization, and these policies can succeed only with widespread bipartisan support. Since the late 1980s, climate change has become a strongly polarizing issue in the United States. However, overall support for climate policy is high, with 66-80% of Americans supporting climate policies. Curiously, 80-90% of Americans underestimate public support for these policies, estimating the prevalence of support to be as low as 37-43%. (Sparkman et al. Nature communications 13.1 (2022): 4779.) The implications of such widespread misperception range from individual behaviors to legislative outcomes. Supporters of climate policy are more likely to self-silence if they believe their peers do not support it, and politicians are less likely to promote policies they believe to be unpopular. Here we present an agent-based social-network model of public perception of support for climate policy grounded in previous empirical studies and opinion surveys. We find that homophily effects alone do not explain widespread misperception. However, our network analysis suggests that disproportionate representation of opposition to climate policy among central nodes can offer a potential explanation for underestimation of public support. In order to assess the validity of this assumption in the real world, we explore the coverage of climate policy in U.S. news media in order to inform our model. Additionally, we explore the effects of self-silencing on misperception.
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https://cuboulder.zoom.us/j/94124750833?pwd=aEYyc2dsUUptbWxZY1FNTXBrbnJyQT09
Meeting ID: 941 2475 0833
Passcode: DynSys
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