The influence of prior knowledge and distributional justice messaging on recipient cognition
Keegan, Michael Garry
Keegan, Michael Garry
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Publication Date
2019-06-18
Type
Thesis
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Abstract
This thesis examines how recipient cognition is influenced by prior knowledge when presented with a distributional justice message. It is hypothesised the cognitive response of high prior knowledge recipients to the advocacy of a counter-attitudinal message can lead to attitude moderation in the desired direction. There is a lack of empirical evidence identifying how prior knowledge biases the evaluation of persuasive communications. The research employs a quantitative in-person survey of householders located in close proximity to the proposed route of a controversial high-voltage overhead electricity line. Ability and motivational variables of the Elaboration Likelihood Model of Persuasion are measured. The counter-attitudinal message presented relates to the provision of ‘community gain’. The findings support the hypothesis that the levels of attitude moderation to the advocacy of a counter-attitudinal persuasive distributive justice message correlates with the levels of prior knowledge of message recipients. High prior knowledge receivers are not a homogenous group in how they cognitively process a new issue-relevant persuasive message, and have the capacity to moderate their attitude when presented with a persuasive message. The extent of receptivity or resistance to a new counter-attitudinal persuasive message correlates to the message receiver’s level of prior knowledge, and their elaboration valence is dependent on their level of prior knowledge to the attitude topic. This research demonstrates distributive justice initiatives such as community gain messaging and delivery, if communicated effectively, can assist in moderating attitudes in controversial circumstances. It increases the capacity to address community acceptance challenges, which are key constraints to infrastructure development.
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NUI Galway
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Attribution-NonCommercial-NoDerivs 3.0 Ireland