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When can scientific studies promote consensus among conflicting stakeholders?
Mitchell J Small1, Ümit Güvenç, Michael L DeKay
1Department of Engineering & Public Policy, Carnegie Mellon University, Pittsburgh, PA, USA.
Summary
Scientific studies often fail to resolve stakeholder conflicts. An extended Bayesian decision model can predict consensus probability by incorporating differing beliefs, valuations, and trust in study efficacy, guiding decision-making processes.
Area of Science:
- Decision Analysis
- Risk Management
- Environmental Science
Background:
- Scientific studies are intended to inform policy and management decisions.
- However, conflicting stakeholders often fail to reach agreement, even with scientific input.
- Trust in the objectivity and efficacy of scientific studies is crucial for consensus-building.
Purpose of the Study:
- To review factors influencing trust in scientific studies within conflict-ridden analytical-deliberative processes.
- To extend the traditional Bayesian decision model to incorporate these trust factors.
- To predict consensus probabilities and identify pathways to increase them.
Main Methods:
- Review of factors affecting trust in scientific studies.
- Extension of the traditional Bayesian decision model.
- Incorporation of stakeholder differences in prior beliefs, outcome valuations, and study efficacy assessments (false positive/negative rates).
Main Results:
- The extended Bayesian model predicts stakeholder-specific preposterior probabilities of consensus.
- The model identifies pathways for increasing consensus probabilities.
- It highlights interactions between risk/benefit perceptions, scientific beliefs, and trust in studies.
Conclusions:
- The extended Bayesian framework offers insights into the value of scientific information in decision-making.
- It helps identify conditions under which consensus can be achieved among conflicting stakeholders.
- The method is illustrated with an example of managing electromagnetic field risks.
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