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Punishment can serve as a form of communication: People use punishment to express information to its recipients and interpret punishment between third parties as having communicative content. Prior work on the expressive function of punishment has primarily investigated the capacity of punishment in general to communicate a single type of message – e.g., that the punished behavior violated an important norm. The present work expands this framework by testing whether different types of punishment communicate different messages. We distinguish between person-oriented punishments, which seek to harm the recipient, and action-oriented punishments, which seek to undo a harmful action. We show that people interpret action-oriented punishments, compared to person-oriented punishments, to indicate that the recipient will change for the better (Study 1). The communicative theory can explain this finding if people understand action-oriented punishment to send a message that is more effective than person-oriented punishment at causing such a change. Supporting this explanation, inferences about future behavior track the recipients' beliefs about the punishment they received, rather than the punisher's intentions or the actual punishment imposed (Study 2). Indeed, when actual recipients of a person-oriented punishment believed they received an action-oriented punishment and vice versa, predictions of future behavior tracked the recipients' beliefs rather than reality, and judgments about what the recipients learned from the punishments mediated this effect (Study 3). Together, these studies demonstrate that laypeople think different types of punishment send different messages to recipients and that these messages are differentially effective at bringing about behavioral changes.
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Crowdsourcing to analyze belief systems underlying social issues
People’s beliefs and attitudes about social and scientific issues, such as capital punishment and climate change, appear to form complex but generally coherent networks. Understanding the nature of these networks is a prerequisite for designing interventions for changing beliefs on the basis of rational arguments and evidence. It is therefore important to develop methods to represent and analyze the form and nature of belief networks, which may not be explicitly verbalizable. Adopting an emerging approach that utilizes crowdsourcing to develop educational interventions, we mined discussions from the Reddit forum Change My View to determine which beliefs and types of information underlie people’s attitudes about capital punishment. By combining computational analyses based on a topic model with more qualitative assessments of the extracted topics, we found that moral arguments are more prevalent than statistical or data-based arguments. The present study serves as a test case for the open sourced software crowdpy, a Python toolkit for running naturalistic studies on the web, which will enable other researchers to use crowdsourcing in their research. This approach sets the stage for research exploring potential interventions to change people’s beliefs.
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- Award ID(s):
- 1827374
- PAR ID:
- 10157636
- Date Published:
- Journal Name:
- Proceedings of the Annual Conference of the Cognitive Science Society
- ISSN:
- 1069-7977
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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