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Book Chapter

Misinformation and disinformation in statistical methodology for social sciences: causes, consequences and remedies

  • Giulio Giacomo Cantone
  • Venera Tomaselli

The present is an introductory summary on the topic of misinformative and fraudolent statistical inferences, in the light of recent attempts to reform social sciences. The manuscript is focused is on the concept of replicability, that is the likelihood of a scientific result to be reached by two independent sources. Replication studies are often ignored and most of the scientific interest regards papers presenting theoretical novelties. As a result, replicability happens to be uncorrelated with bibliometric performances. These often reflect only the popularity of a theory, but not its validity. These topics are illustrated via two case studies of very popular theories. Statistical errors and bad practices are discussed. The consequences of the practice of omitting inconclusive results from a paper, or 'p-hacking', are discussed. Among the remedies, the practice of preregistration is presented, along with attempts to reform peer review through it. As a tool to measure the sensitivity of a scientific theory to misinformation and disinformation, multiversal theory and methods are discussed.

  • Keywords:
  • replication crisis,
  • research evaluation,
  • p-hacking,
  • preregistration,
  • multiverse analysis,
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Giulio Giacomo Cantone

University of Catania, Italy - ORCID: 0000-0001-7149-5213

Venera Tomaselli

University of Catania, Italy - ORCID: 0000-0002-2287-7343

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  • Publication Year: 2023
  • Pages: 53-58
  • Content License: CC BY 4.0
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  • Publication Year: 2023
  • Content License: CC BY 4.0
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Chapter Information

Chapter Title

Misinformation and disinformation in statistical methodology for social sciences: causes, consequences and remedies

Authors

Giulio Giacomo Cantone, Venera Tomaselli

Language

English

DOI

10.36253/979-12-215-0106-3.10

Peer Reviewed

Publication Year

2023

Copyright Information

© 2023 Author(s)

Content License

CC BY 4.0

Metadata License

CC0 1.0

Bibliographic Information

Book Title

ASA 2022 Data-Driven Decision Making

Book Subtitle

Book of short papers

Editors

Enrico di Bella, Luigi Fabbris, Corrado Lagazio

Peer Reviewed

Publication Year

2023

Copyright Information

© 2023 Author(s)

Content License

CC BY 4.0

Metadata License

CC0 1.0

Publisher Name

Firenze University Press, Genova University Press

DOI

10.36253/979-12-215-0106-3

eISBN (pdf)

979-12-215-0106-3

eISBN (xml)

979-12-215-0107-0

Series Title

Proceedings e report

Series ISSN

2704-601X

Series E-ISSN

2704-5846

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