Climate change is one of the biggest challenges facing the global agricultural food system at the current moment. While scientists agree that anthropogenic climate change is a critical issue, many United States residents remain skeptical, presenting a significant communication challenge. Understanding the factors influencing public perceptions of climate change are essential to informing agricultural and environmental communication efforts if they are to be effective at mitigating its effects. Previous studies have identified political affiliation and ideology as key predictors for climate change perceptions; however, understanding more detailed components of political ideology and affiliation could strengthen the predictive capacity of these variables. The current study explored the predictive capacity of perceptions of government control on environmental behavior related to political affiliation and ideology to inform effective communication based on climate change knowledge. Using an online survey of U.S. residents, political ideology and affiliation were found to be important predictors of climate change knowledge but including perceptions of government control on environmental behavior expanded their predictive capacity. Agricultural and environmental communicators are encouraged to integrate more nuanced components of political affiliation and ideology, such as perceptions of government control, into their messaging strategies to increase potential message uptake in the midst of a politically polarized media environment. Future research should identify and explore other aspects of political affiliation and ideology, such as economic and social factors, that may influence the public’s perception of climate change and its related policy implications.
Sanders, Catherine E.; Gibson, Kristin; and Lamm, Alexa J.
"Perceived Government Control and its Influence on Climate Change Knowledge and Perceptions: Applications for Effective Communication,"
Journal of Applied Communications:
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 4.0 License.