Hypothesis
  • The Hypothesis White Paper
  • Introduction
    • Thesis
  • The Hypothesis Vision
    • Defining "Trust" in a "Post-Truth" World
    • A New Way To Interact With Media
    • Interweaving Incentives With Foresight and Usefulness
    • A New Model of Accountability
    • Section Summary
  • Building a platform based on openness & transparency
    • Redefining “Community-Powered”
      • Formulating Questions
      • Context
      • Question Resolution
      • Groups
    • Data-Driven Gamification
      • Foresight
      • Usefulness
      • Quality of Research
      • Knowledge Metric
    • Protecting User Privacy
  • Monetization
    • A Note on Monetization
    • Subscriptions
    • Foresight API & the future of Hypothesis
      • Cultivating Oracles & User-Earned Revenue
      • The Media’s Monetization Problem
  • Concerns
    • Platform Limitations
    • Dangers of Bias
  • Conclusion
    • Closing Remarks
    • Roadmap
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  1. Building a platform based on openness & transparency
  2. Data-Driven Gamification

Quality of Research

An additional metric can be calculated by extrapolating on the Usefulness data point. Called Quality of Research Rating, this number indicates the overall quality of a given question’s research sources by calculating their total mean Usefulness. The Quality of Research Rating can give users a better idea about how accurately publishers are covering a given topic, as well as how good of a job their peers did at collecting research.

While Hypothesis intends to be transparent about as much of its technology as possible, the processes describing Quality of Research are currently under development and cannot be made public. Relevant stakeholders may contact miles@hypothesis.fyi for more information regarding Hypothesis algorithms.

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Last updated 3 years ago

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