复杂适应系统
战略沟通
计算机科学
过程管理
管理科学
知识管理
业务
政治学
公共关系
工程类
人工智能
标识
DOI:10.31235/osf.io/a32z9
摘要
Science communication plays a crucial role in maintaining public trust in science amid complex societal challenges. This study addresses a gap in understanding science communication dynamics by conceptualizing it as a complex adaptive system of actors. It introduces the CASSCO (Complex Adaptive System of Science Communication) model, which integrates complex adaptive systems theory with game theory to analyze strategic interactions in science communication. The model encompasses decision-making processes, impact evaluation, and learning mechanisms among actors, distinguishing between institutional and organizational roles across three communica-tion modes: dissemination, dialogue, and participation. By applying the CASSCO model to two scenarios - citizen science and generative AI – the study demonstrates its potential for predicting non-linear dynamics and emergent outcomes in science communication. This approach yields insights into the impact of communication strategies on public trust and contestations of science. The CASSCO model serves as a strategic thinking template, enabling actors to select strategies while considering the behaviors of others. The study concludes with theoretical and practical implications, model limitations, and future research directions.
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