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Evaluating science communication

Authors: Baruch Fischhoff;

Evaluating science communication

Abstract

Effective science communication requires assembling scientists with knowledge relevant to decision makers, translating that knowledge into useful terms, establishing trusted two-way communication channels, evaluating the process, and refining it as needed. Communicating Science Effectively: A Research Agenda [National Research Council (2017)] surveys the scientific foundations for accomplishing these tasks, the research agenda for improving them, and the essential collaborative relations with decision makers and communication professionals. Recognizing the complexity of the science, the decisions, and the communication processes, the report calls for a systems approach. This perspective offers an approach to creating such systems by adapting scientific methods to the practical constraints of science communication. It considers staffing (are the right people involved?), internal collaboration (are they talking to one another?), and external collaboration (are they talking to other stakeholders?). It focuses on contexts where the goal of science communication is helping people to make autonomous choices rather than promoting specific behaviors (e.g., voter turnout, vaccination rates, energy consumption). The approach is illustrated with research in two domains: decisions about preventing sexual assault and responding to pandemic disease.

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Keywords

Biomedical Research, Information Dissemination, Communication, Science, Decision Making, Sex Offenses, Models, Theoretical, Humans, Pandemics

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    77
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
77
Top 1%
Top 10%
Top 10%
bronze