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What Fairies Can Teach Us About Science

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Author: Dr. Jonathan Berman | Category: Research Integrity | May 20, 2016

Arthur Conan Doyle can be fairly regarded as a smart guy. He was a physician and wrote over 60 books. He invented the Sherlock Holmes character that has endured to this day in the public consciousness as a paragon of reason. 

Many familiar with Doyle’s works of fiction may not realize that one of his chief interests was the spiritualist movement of the day and psychic phenomena.

In 1919-1920, Doyle became involved in the investigation of a pair of photographs that had begun circulating in the spiritualist community.

These photographs seemed to show two young women, Frances Griffiths and Elsie Wright playing with fairies. 

These images were later admitted to have been hoaxed by tracing drawings onto cardboard standups, which was cheaper than a copy of photoshop in 1917. 

Doyle latched onto the photographs as positive proof supporting his beliefs and in 1920 he commissioned three more photographs from the women (using a provided camera with secretly marked photographic plates), and upon examining 

the results published an article in The Strand arguing that the evidence warranted a prima facie acceptance of the photographs until proved otherwise (a reverse of the normal scientific principle of placing the burden of proof on the claimant).

As easy as it is for us to mock and criticize Doyle today, and he received his share of criticism at the time as well, there are parallels between the mistake the Doyle made and scientists who make the same mistakes to this day. Doyle was looking for evidence to confirm his beliefs, rather than evidence to disconfirm it.

The cases of bad science that make the news are the rarest and most extreme examples (otherwise they would not make the news). It isn’t data falsification we have to worry about so much as the subtle ways that biases creep into our data and interpretation and fool us in the same way that Doyle was fooled.

In 2015, the Reproducibility Project published replications of over 100 psychological studies and found only 39 percent to be replicable. The problem isn’t isolated to psychology. Although the cost of replication in biomedical sciences is much higher, earlier studies have shown similar rates of low reproducibility.

These problems are deeper than simple experimenter bias. The majority of biological publications either misuse or improperly interpret statistics.The National Institutes of Health (NIH) continues to fund a center devoted to throwing money at medical treatments that don’t meet the scientific standards for evidence. 

Sometimes these are genuine mistakes, but the prevalence of journals that will not report negative or confirmatory results, or accept results only on the basis of an arbitrary p-value cutoff suggest a systemic unwillingness to look at the systemic problems in science.

In the early 20th century, Doyle maintained a friendship with the skeptic Harry Houdini (also noted as a magician). Houdini traveled the world exposing the tricks used by spirit mediums. Eventually, the séances that were in vogue in the Victorian parlor withered in the light of skeptical investigation and retreated to the status of fringe diversion.

Scientists are driven by all of the same fears, worries, and hidden vanities that drive all human behavior. We are asked to so often to justify our desire to participate in science that we internalize a mantra about the love of discovery, puzzle solving, and human health. 

Perhaps we would be better off to internalize a reflection on our personal motivations, and how they influence our results. If some day your friend tells you that data interpretation is akin to believing in fairies, don’t double down on your position. 

At least hear her out because mostly Houdini was right.

 Dr. Jonathan Berman is a postdoctoral fellow at the University of Texas Health Science Center San Antonio in the laboratory of James Stockand and in the Department of Physiology. Dr. Berman's research has focused on the molecular origins of hypertension, and will expand to the physiology whole body magnesium homeostasis and associated diseases.



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