The scientific establishment positions itself as an objective authority that demands our trust, but their actions over the course of the past two decades certainly don’t suggest they are worthy of it. From an old scandal in climate science to a new one concerning the pandemic, they hide the data that doesn’t support their conclusions and release only what aligns with their goals.
On November 6, 1999 the director of the East Anglia Climate Research Unit, Phil Jones, sent an email to his colleagues that read, “I’ve just completed Mike’s Nature trick of adding in the real temps to each series for the last 20 years (ie from 1981 onwards) and from 1961 for Keith’s to hide the decline.” Mr. Jones was referring to the infamous “hockey stick” graph which purported to show a rapid increase in temperatures in the second half of the twentieth century. The “trick” he referenced was an intentional mixing of data sets to support their pre-existing conclusion. The chart relied on actual, observed temperatures in some parts and interpolated data, known as a proxy series, for other parts to make it appear the increase in temperature was more pronounced and rapid than it was using a single set. Needless to say, this is highly unusual. When a data set is presented, it is assumed the data was obtained from the same source, using the same calibrations, and collected using the same methodology, but here was a chart that mixed and matched data, some of it real and observed, some of it derived from observations of tree rings and other sources.
Further, this same “trick” had been applied to at least two other data sets. At the time, Mr. Jones had been working on a diagram for the World Meteorological Association, a body considered the “authoritative voice on the state and behavior of the Earth’s atmosphere.” Four months later, it was included on the cover of an annual report with the claim “all the reconstructions … indicate that against the background of the millennium as a whole, the 20th century was unusually warm.” The release of this email and others prompted a scandal that came to be known as Climategate, one which hasn’t been resolved to this day despite claims to the contrary. When confronted with their own words, the scientists responded by claiming “trick” didn’t refer to anything nefarious, merely a “a good way to deal with a problem.” “Hiding” was just a “poor choice of words.” Only using part of the proxy series was “well known” and “completely appropriate” because the proxy set “diverges from the temperature records.” Of course, this divergence is entirely the point. If one series diverges from the other, what meaningful observation can we possibly make by using both in a single chart?
The lead author of the “hockey stick” graph, Michael Mann, responded to some of these claims five years later. He claimed that cutting off the proxy studies should only be used sparingly, because “evidence incapable of resolving trends in recent decades…cannot meaningfully address the question of whether late 20th century warmth is anomalous in a long-term and large-scale context,” but this begs a similar question: If they are incapable of resolving the trends, why use them at all? He continued to deny that the mixing and matching actually occurred, maligning those that questioned the dubious methodology, “No researchers in this field have ever, to our knowledge, ‘grafted the thermometer record onto’ any reconstruction. It is somewhat disappointing to find this specious claim (which we usually find originating from industry-funded climate disinformation websites) appearing in this forum.” This, however, is precisely what they did: The World Meteorological Organization presented the graph as a single data series, with no means to differentiate the different sources.
Ultimately, the entire episode had more than a little whiff of Shakespeare’s famous maxim “the lady doth protest too much, methinks.” Whatever their reasoning or excuses, the simple fact remains, whether trick or technique, scientifically legitimate or not, one thing is inescapable: The final product was assembled in a way to support their pre-existing conclusion. They made these choices with a specific goal in mind, meaning they didn’t objectively follow where the data lead. Instead, they chose the data that supported where they always wanted to go, and took steps to hide their reasoning, or at least minimize its presence when the conclusion reached the public. To some extent, this is human nature. We all have cognitive biases and organize incoming data around our existing beliefs. Scientists, however, are supposed to be different, more objective, following facts rather than choosing them, letting the data dictate the conclusion rather than the other way around, or at least that’s what they claim and why they are supposed to command so much respect. If scientists are free to mix and match data to support their conclusion without informing the public, however, how is the public supposed to trust what they report and conclude?
Fast forward twenty three years and the story is much the same, though this time the importance of the manipulated data is far more pressing and immediate than what might happen with the weather 100 years from now. The coronavirus pandemic has disrupted almost every human life on the entire planet for close to two full years, and the living are the lucky ones when close to 6 million people succumbed to the disease. Throughout it all, many public health experts, politicians, and the mainstream media have urged us to rely on the Centers for Disease Control and Prevention for unbiased, objective, and data-driven guidance on the precautions we should take and the restrictions we should endure to slow the spread of the virus. Last week, Press Secretary Jen Psaki put it this way, “The CDC guidance follows data and science. And data and science moves at the speed of data and science.” Now, none other than The New York Times begs to differ, publishing an explosive report “The C.D.C. Isn’t Publishing Large Portions of the Covid Data It Collects,” and noting that “The agency has withheld critical data on boosters, hospitalizations and, until recently, wastewater analyses.”
These are far from accidental omissions either. On boosters, for example, “When the C.D.C. published the first significant data on the effectiveness of boosters in adults younger than 65 two weeks ago, it left out the numbers for a huge portion of that population: 18- to 49-year-olds, the group least likely to benefit from extra shots, because the first two doses already left them well-protected.” In other words, the CDC knew full well that boosters weren’t really required for younger Americans, who have very little risk of a serious case and next-to-no risk of death from the virus, especially if they are vaccinated. Simply telling the truth, however, would have undercut the crusade to vaccinate everyone once, twice, three times, and now there are even rumors of a fourth planned for the fall. Instead, they chose to omit the largest portion of the data set to support their pre-existing conclusion that everyone needed to be boosted as soon as possible. This is not a decision without consequence: Millions of unnecessary shots were administered at great cost. These shots could have been used in older or higher risk populations, here or around the world. Nor is any shot without potential risk of its own. Someone likely suffered an adverse event or possibly even died for absolutely no reason at all, except boosters for all was the strategy they chose to pursue regardless of the facts.
The New York Times also reported that the CDC has been collecting yet withholding data on so-called breakthrough infections, those that occur after a person has been fully vaccinated. In their words, “the C.D.C. has been routinely collecting information since the Covid vaccines were first rolled out last year, according to a federal official familiar with the effort. The agency has been reluctant to make those figures public, the official said, because they might be misinterpreted as the vaccines being ineffective.” The idea that data might be “misinterpreted” is a common theme. Kristen Nordlund, a spokeswoman for the CDC, told the Times they have been slow to release this data “because basically, at the end of the day, it’s not yet ready for prime time.” She noted the “priority when gathering any data is to ensure that it’s accurate and actionable.” Note the term, “actionable.” Putting it another way, they decide how you should act and then release data to support those actions. Ms. Nordlund also repeated the “misinterpreted” fear.
Incredibly, the Times is now comfortable claiming without any irony or shame that the CDC is merely a “political organization.” They quote Samuel Scarpino, the managing director of pathogen surveillance at the Rockefeller Foundation’s Pandemic Prevention Institute. “The C.D.C. is a political organization as much as it is a public health organization. The steps that it takes to get something like this released are often well outside of the control of many of the scientists that work at the C.D.C.” This alone should be shocking news: The entire time President Trump was in office we were told repeatedly that the CDC was a non-political, data-driven organization staffed with objective experts. Indeed, that is the claim Ms. Psaki made last week, but suddenly it’s as political as anything else. This brings us back to the original question: Why should we trust any of these so-called experts when none other than The New York Times admits they are employed by a political organization? For close to two years now, criticism of the CDC and Dr. Anthony Fauci was often countered with the canard that you were undermining trust in vital institutions. The same argument has been applied to the FBI and the Department of Justice, even as we learn more and more that they knowingly recycled data sourced by the opposition candidate to mount one of the most destructive investigations in the modern era. Trust, however, needs to be earned and, in my opinion at least, they have done very little to earn it, nor do they seem to care. Instead, they’ll keep telling you they are hiding the data for your own good, just trust them regardless of the facts.