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Category: Project

Description: Moral reframing has been put forward as a tool for people to use to gather support on policy issues from politically (and ideologically) dissimilar others. Essentially, moral reframing utilises wording/arguments that tap into the target audience’s morality to persuade them to support policies/positions they typically wouldn’t otherwise. As an example, in the US, one could morally reframe the issue of pro-environmentalism with wording/arguments about patriotism and purity to sway ideologically conservative Americans to show more support for pro-environmental action (on average, US conservatives are less pro-environmental than US liberals). Previous experimental research has found that morally reframed messages/arguments are, in general, more effective at changing people's attitudes than non-morally reframed messages. However, there has been no focus on whether people use morally reframed messages to persuade politically dissimilar others in the first place (and if so, what predicts this behaviour?). Ultimately, the validity of moral reframing as a political persuasion tool depends, in part, on addressing this research gap. In this study, I will invite ideologically liberal, pro-environmental participants to imagine a hypothetical scenario and read two short messages that promote pro-environmental action. These messages differ only in their moral framing: one uses liberal wording and values; the other, conservative wording/values. Participants will then be asked to choose between them (i.e., select the message they would communicate to a conservative audience to be more open to, and supportive of, pro-environmental action). Afterwards, participants will be asked to answer questions about the messages; the reason behind their choice; how they feel about using their message choice; and how they would feel if they had to use the other message (hypothetically). They will conclude this study with some questions about their position on (and associaiton with) environmentalists and about their demographics (i.e., age and gender).