Junk science is spurious or fraudulent scientific data, research, or analysis. The concept is often invoked in political and legal contexts where facts and scientific results have a great amount of weight in making a determination. It usually conveys a pejorative connotation that the research has been untowardly driven by political, ideological, financial, or otherwise unscientific motives. The concept was popularized in the 1990s in relation to expert testimony in civil litigation. More recently, invoking the concept has been a tactic to criticize research on the harmful environmental or public health effects of corporate activities, and occasionally in response to such criticism. In some contexts, junk science is counterposed to the "sound science" or "solid science" that favors one's own point of view. Junk science has been criticized for undermining public trust in real science. Junk science is not the same as pseudoscience.
Definition Junk science has been defined as:
"science done to establish a preconceived notion—not to test the notion, which is what proper science tries to do, but to establish it regardless of whether or not it would hold up to real testing." "opinion posing as empirical evidence, or through evidence of questionable warrant, based on inadequate scientific methodology." "methodologically sloppy research conducted to advance some extrascientific agenda or to prevail in litigation."
Motivations Junk science happens for different reasons: researchers believing that their ideas are correct before proper analysis (a sort of scientific self-delusion or drinking the Kool-Aid), researchers biased with their study designs, and/or a "plain old lack of ethics". Being overly attached to one's own ideas can cause research to veer from ordinary junk science (e.g., designing an experiment that is expected to produce the desired results) into scientific fraud (e.g., lying about the results) and pseudoscience (e.g., claiming that the unfavorable results actually proved the idea correct). Junk science can occur when the perpetrator has something to gain from arriving at the desired conclusion. It can often happen in the testimony of expert witnesses in legal proceedings, and especially in the self-serving advertising of products and services. These situations may encourage researchers to make sweeping or overstated claims based on limited evidence.
History The phrase junk science appears to have been in use prior to 1985. A 1985 United States Department of Justice report by the Tort Policy Working Group noted:
The use of such invalid scientific evidence (commonly referred to as 'junk science') has resulted in findings of causation which simply cannot be justified or understood from the standpoint of the current state of credible scientific or medical knowledge. In 1989, the climate scientist Jerry Mahlman (Director of the Geophysical Fluid Dynamics Laboratory) characterized the theory that global warming was due to solar variation (presented in Scientific Perspectives on the Greenhouse Problem by Frederick Seitz et al.) as "noisy junk science." Peter W. Huber popularized the term with respect to litigation in his 1991 book Galileo's Revenge: Junk Science in the Courtroom. The book has been cited in over 100 legal textbooks and references; as a consequence, some sources cite Huber as the first to coin the term. By 1997, the term had entered the legal lexicon as seen in an opinion by Supreme Court of the United States Justice John Paul Stevens:
An example of 'junk science' that should be excluded under the Daubert standard as too unreliable would be the testimony of a phrenologist who would purport to prove a defendant's future dangerousness based on the contours of the defendant's skull. Lower courts have subsequently set guidelines for identifying junk science, such as the 2005 opinion of United States Court of Appeals for the Seventh Circuit Judge Frank H. Easterbrook: Positive reports about magnetic water treatment are not replicable; this plus the lack of a physical explanation for any effects are hallmarks of junk science. As the subtitle of Huber's book, Junk Science in the Courtroom, suggests, his emphasis was on the use or misuse of expert testimony in civil litigation. One prominent example cited in the book was litigation over casual contact in the spread of AIDS. A California school district sought to prevent a young boy with AIDS, Ryan Thomas, from attending kindergarten. The school district produced an expert witness, Steven Armentrout, who testified that a possibility existed that AIDS could be transmitted to schoolmates through yet undiscovered "vectors". However, five experts testified on behalf of Thomas that AIDS is not transmitted through casual contact, and the court affirmed the "solid science" (as Huber called it) and rejected Armentrout's argument. In 1999, Paul Ehrlich and others advocated public policies to improve the dissemination of valid environmental scientific knowledge and discourage junk science:
The Intergovernmental Panel on Climate Change reports offer an antidote to junk science by articulating the current consensus on the prospects for climate change, by outlining the extent of the uncertainties, and by describing the potential benefits and costs of policies to address climate change. In a 2003 study about changes in environmental activism regarding the Crown of the Continent Ecosystem, Pedynowski noted that junk science can undermine the credibility of science over a much broader scale because misrepresentation by special interests casts doubt on more defensible claims and undermines the credibility of all research. In his 2006 book Junk Science, Dan Agin emphasized two main causes of junk science: fraud, and ignorance. In the first case, Agin discussed falsified results in the development of organic transistors:
As far as understanding junk science is concerned, the important aspect is that both Bell Laboratories and the international physics community were fooled until someone noticed that noise records published by Jan Hendrik Schön in several papers were identical—which means physically impossible. In the second case, he cites an example that demonstrates ignorance of statistical principles in the lay press:
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