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arxiv: 1702.04219 · v1 · pith:NH3VMLJAnew · submitted 2017-02-10 · 💻 cs.CY · cs.HC

Experiments on Crowdsourcing Policy Assessment

classification 💻 cs.CY cs.HC
keywords policycrowdsnon-expertexperimentsrecruitedassessmentmeasurescontext
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Can Crowds serve as useful allies in policy design? How do non-expert Crowds perform relative to experts in the assessment of policy measures? Does the geographic location of non-expert Crowds, with relevance to the policy context, alter the performance of non-experts Crowds in the assessment of policy measures? In this work, we investigate these questions by undertaking experiments designed to replicate expert policy assessments with non-expert Crowds recruited from Virtual Labor Markets. We use a set of ninety-six climate change adaptation policy measures previously evaluated by experts in the Netherlands as our control condition to conduct experiments using two discrete sets of non-expert Crowds recruited from Virtual Labor Markets. We vary the composition of our non-expert Crowds along two conditions: participants recruited from a geographical location directly relevant to the policy context and participants recruited at-large. We discuss our research methods in detail and provide the findings of our experiments.

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