Which reveals the dangerous precedent: science by consensus. Truth be told, scientific consensus is an oxymoron as a single research paper can falsify decades of fashionable or agreed-upon science.
In the words of the late scientist/author Michael Crichton, “I regard consensus science as an extremely pernicious development that ought to be stopped cold in its tracks. Historically, the claim of consensus has been the first refuge of scoundrels; it is a way to avoid debate by claiming that the matter is already settled ... Consensus is the business of politics. Science, on the contrary, requires only one investigator who happens to be right, which means that he or she has results that are verifiable by reference to the real world ... The greatest scientists in history are great precisely because they broke with the consensus.”
Perhaps the most famous and credible example of what can go wrong is the tale of “junk science” environmentalism used to have the pesticide DDT banned – leading to the horrible deaths of millions of individuals who were stricken by diseases borne by mosquitos.
Let’s consider some of the biases that may be involved.
The peer-review bias … few people understand that peer-review is a journal publishing process designed to preserve the journal’s reputation by weeding out craziness and ensuring that the material presented is clear and understandable to its qualified audience. Reviewers do not replicate experiments, they do not independently analyze the data, nor do they vouch for the author’s conclusions. The fact that research appears in a well-respected journal that uses the peer-review process is almost meaningless; especially when the reviewers are colleagues of the author or have substantially the same viewpoint.
The correlation bias … the results of applying statistical methodologies to a dataset may produce some result, but may not answer fundamental questions. First, is the variable or variables under examination the correct variable(s) to test in a world with a multiplicity of both dependent and independent variables? Second, does correlation imply causation? And third, what is the probability that the result is not an error? All recreational drug users drink water, and the correlation is one-hundred percent. But the real question is, while drinking water correlates with drug use, does drinking water cause drug use?
The inherent sponsorship bias … it is well known that institutions, researchers, and projects that are aligned with the agenda of the sponsor are more likely to be funded than research the falsifies previous significant and costly research. And, as we have seen numerous times in the past, research that is adverse to the sponsor’s position is either abandoned or buried in reams of irrelevancy. This leads to a strategic error in thinking. Since pro-research papers will outnumber con-research papers, can one rely on the number of papers published to determine a scientific truth?
Searching the literature is not always the answer.
And, one might suspect that the venality of the well-paid attorneys who may be betting on some form of pre-trial multi-million dollar settlement might be the impetus for the cases.
Already, I am seeing attorneys soliciting cases on television using the opening "Legal Alert" and widely advertising their 1-800 number to farmers, landscapers, and heavy exposure residential users. Using the tagline, "If you or someone you love has been diagnosed with Non-Hodgkin's Lymphoma after being exposed to a popular weed killer, you may be entitled to compensation. Call for more information."
