Piltdown Man: The Forgery That Fooled Science - Episode Hero Image

Piltdown Man: The Forgery That Fooled Science

Original Title: Homo deceptus: Science's Dirty Little Secret

Resources

Resources & Recommendations

Books

  • "The Piltdown Man Hoax: Case Closed" by Miles Russell - This book details Charles Dawson's extensive history of creating fakes, providing a strong case for him as the Piltdown fraudster.
  • "Unraveling Piltdown" by John Evangelist Walsh - A key source mentioned for understanding the Piltdown fraud.

Articles & Papers

  • "Cluster Fake" (Data Colada blog post) - This blog post exposed manipulated data in studies related to dishonesty, specifically highlighting issues in papers co-authored by Dan Ariely and Francesca Gino.

People Mentioned

  • Charles Dawson (Amateur Geologist) - The primary suspect in the Piltdown Man hoax, known for a long history of creating fraudulent "discoveries."
  • Arthur Woodward (Keeper of the Museum's Geology Department) - Initially involved in the Piltdown Man discovery and later knighted for his contributions, he was presented as a potential dupe in Dawson's frauds.
  • Joseph Weiner (Professor of Physical Anthropology at Oxford) - The scientist who meticulously investigated the Piltdown Man relics and ultimately uncovered the fraud in 1953.
  • Kenneth Oakley (Guardian of the Piltdown bones at the Natural History Museum) - He was instrumental in providing access to the Piltdown bones for Weiner's investigation and confirming the signs of artificial abrasion.
  • Dan Ariely (Behavioral Scientist) - Mentioned as a superstar of behavioral science whose co-authored work contained fraudulent data, though he denies culpability.
  • Francesca Gino (Behavioral Scientist, Harvard University) - Another superstar of behavioral science whose research was found to contain manipulated data, leading to her suspension and legal action.
  • Joe Simmons (Psychologist, Data Colada team) - One of the psychologists behind the "Data Colada" blog, which exposed fraudulent data in social science research.
  • Leif Nelson (Psychologist, Data Colada team) - Another member of the "Data Colada" team, involved in uncovering research fraud.
  • Uri Simonsohn (Psychologist, Data Colada team) - The third member of the "Data Colada" team, who alongside Simmons and Nelson, identified issues in academic papers.
  • Don Poldermans (Dutch Researcher, Erasmus Medical School) - A researcher found to have used fictitious and unreliable data in studies concerning major surgery and the use of beta blockers, with potentially deadly consequences.
  • Miles Russell (Historian) - Author of "The Piltdown Man Hoax: Case Closed," which details Dawson's fraudulent activities.
  • Sir Arthur Conan Doyle (Author) - Mentioned as a neighbor of Charles Dawson and a speculative, though unlikely, suspect in the Piltdown fraud.

Organizations & Institutions

  • Natural History Museum (London) - The institution where the Piltdown Man relics were housed and where the fraud was eventually uncovered.
  • Oxford University - Joseph Weiner's affiliation, where he conducted the critical experiments that exposed the Piltdown fraud.
  • The Royal Society - An organization that awarded Arthur Woodward for his supposed discovery of Piltdown Man.
  • The Linnean Society - Another organization that awarded Arthur Woodward.
  • Behavioral Insights Team (The Nudge Unit) (UK government) - This team attempted to replicate a behavioral science finding in Guatemala but found it didn't work, leading to scrutiny of the original research.
  • Harvard University - Francesca Gino's employer, which investigated her for research misconduct and took disciplinary action.
  • Erasmus Medical School - Don Poldermans' employer, which found him to have used fictitious data in his research.

Websites & Online Resources

  • Data Colada (Website) - A website run by three psychologists that critiques sloppy and fraudulent research methods in social science.

Other Resources

  • "When I'm 64" (Song by The Beatles) - Used by the Data Colada team in a satirical demonstration of how flawed statistical techniques could produce nonsensical findings.

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