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A Classification System for Competing Narratives in a Risk Context.

Shital Thekdi1, Terje Aven2

  • 1University of Richmond, Richmond, Virginia, USA.

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|December 5, 2025
PubMed
Summary
This summary is machine-generated.

Understanding narratives, including misinformation and biases, is crucial for risk study integrity. Classifying these narratives improves risk perception and study design for analysts, policymakers, and communicators.

Keywords:
misinformationrisk analysisrisk communication

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Area of Science:

  • Risk analysis
  • Science communication
  • Cognitive science

Background:

  • Risk studies can be influenced by misinformation, biases, and social dynamics, termed narratives.
  • These narratives impact perceived scientific truths, risk concerns, and values, affecting overall risk perception and study quality.
  • Understanding these narratives is vital for effective risk assessment and communication.

Purpose of the Study:

  • To develop a classification system for analyzing narratives in risk studies.
  • To understand how narratives influence risk perception and the perceived quality of risk studies.
  • To inform the design and implementation of risk studies by addressing influential narratives.

Main Methods:

  • Literature review on misinformation, biases, and narratives in risk studies.
  • Development of a narrative classification system.
  • Analysis of how narratives affect risk perception and stakeholder evaluation.

Main Results:

  • Narratives, encompassing concern and value, are integral to risk studies.
  • Narratives can both challenge scientific objectivity and illuminate perceived truths and values.
  • A classification system can help identify and manage narratives influencing risk perception.

Conclusions:

  • Classifying narratives provides evidence to improve risk study design and implementation.
  • Addressing narratives enhances the understanding of risk perception and study quality.
  • This work is valuable for risk analysts, policymakers, and risk communicators.