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Enabling Scientific Crowds: The Theory of Enablers for Crowd-Based Scientific Investigation

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  • Jorge Faleiro

Abstract

Evidence shows that in a significant number of cases the current methods of research do not allow for reproducible and falsifiable procedures of scientific investigation. As a consequence, the majority of critical decisions at all levels, from personal investment choices to overreaching global policies, rely on some variation of try-and-error and are mostly non-scientific by definition. We lack transparency for procedures and evidence, proper explanation of market events, predictability on effects, or identification of causes. There is no clear demarcation of what is inherently scientific, and as a consequence, the line between fake and genuine is blurred. This paper presents highlights of the Theory of Enablers for Crowd-Based Scientific Investigation, or Theory of Enablers for short. The Theory of Enablers assumes the use of a next-generation investigative approach leveraging forces of human diversity, micro-specialized crowds, and proper computer-assisted control methods associated with accessibility, reproducibility, communication, and collaboration. This paper defines the set of very specific cognitive and non-cognitive enablers for crowd-based scientific investigation: methods of proof, large-scale collaboration, and a domain-specific computational representation. These enablers allow the application of procedures of structured scientific investigation powered by crowds, a collective brain in which neurons are human collaborators

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  • Jorge Faleiro, 2018. "Enabling Scientific Crowds: The Theory of Enablers for Crowd-Based Scientific Investigation," Papers 1809.07195, arXiv.org.
    • Handle: RePEc:arx:papers:1809.07195
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    References listed on IDEAS

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    1. John Foster, 2005. "From simplistic to complex systems in economics," Cambridge Journal of Economics, Cambridge Political Economy Society, vol. 29(6), pages 873-892, November.
    2. Jitendra Kumar Rout & Kim-Kwang Raymond Choo & Amiya Kumar Dash & Sambit Bakshi & Sanjay Kumar Jena & Karen L. Williams, 2018. "A model for sentiment and emotion analysis of unstructured social media text," Electronic Commerce Research, Springer, vol. 18(1), pages 181-199, March.
    3. Jorge Faleiro, 2018. "A Language for Large-Scale Collaboration in Economics: A Streamlined Computational Representation of Financial Models," Papers 1809.06471, arXiv.org.
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