Climate Change Interpretive Communities
In collaboration with other groups in Australia and overseas, this project will conduct ‘audience segmentation studies’ to understand the different ways Australians perceive climate change.
Many studies of climate change attitudes simply use a binary model of voting intention combined with belief or disbelief in climate change. However these kinds of surveys do not undercover the complexity of perceptions and how they come about. To address this, this project uses ‘latent profile analysis’ to see how Australia is actually divided into at least five or six different groups on climate change.
In Australia, Morrison, Parton and Hine (2018) have found that the country is divided into six climate change segments: the Alarmed, Concerned, Cautious, Disengaged, Doubtful and Dismissive*, and that these segments are changing over time. Overseas, the Yale Program in Climate Change Communication and the Center for Climate Change Communication at George Mason University have been conducting segmentations studies for over 10 years with their Climate Change in the American Mind research.
We will be building on this kind of work to look at the following characteristics in each of the Australian Segments: values, attitudes, knowledge, behaviour, concern, voting intention and primary media sources for each group. However, we will also be looking at what kinds of messages on climate change engage each of the groups.
Do these groups differ in who they trust to deliver these messages? Are there general messages that work with all groups or if there are six Australia’s do you need six kinds of messages?
You can read about the critical importance of Latent Profile Analysis in our Literature Review of best practice communication of climate science and impacts: Guide for policymakers, published by the Victorian Government Department of Environment, Land, Water and Planning.
* Morrison M, Parton K, Hine DW (2018) Increasing belief but issue fatigue: Changes in Australian Household Climate Change Segments between 2011 and 2016. PLoSONE 13(6): e0197988.