The above image was made with stable diffusion using the prompt 'science laboratory.'
Throughout the pandemic, we were told by the powers that be to trust the science. But science is a process, not a person in whom we can place our faith. This process always produces meaningful data about how the world works, yet correctly interpreting that data isn't always easy or possible. And for a variety of reasons, official interpretations of scientific data appear broadly untrustworthy.
Here's a quote from a 2005 paper by John Ioannidis about this issue:
A research finding is less likely to be true when the studies conducted in a field are smaller; when effect sizes are smaller; when there is a greater number and lesser preselection of tested relationships; where there is greater flexibility in designs, definitions, outcomes, and analytical modes; when there is greater financial and other interest and prejudice; and when more teams are involved in a scientific field in chase of statistical significance. Simulations show that for most study designs and settings, it is more likely for a research claim to be false than true. Moreover, for many current scientific fields, claimed research findings may often be simply accurate measures of the prevailing bias.
If the name Ioannidis sounds familiar, that's because this top notch scientist was an outspoken opponent of lockdown policies, for which he was lambasted by blue news and censored by social media. After disastrous pandemic policies upended everything, WaPo and other legacy news outlets pushed the story that we did too little, not too much, in our efforts to combat the virus. I know there are reasonable people out there who actually believe this. In my mind, I consider them on par with those who believe that the moon landing was faked or that the Earth is flat, because the evidence that pandemic policies were harmful is so glaringly obvious.
Maybe scientific findings have become more trustworthy in recent years. But a new paper in Nature suggests that problems are still widespread. Here's a quote from that one:
By studying the IPD spreadsheets, he judged that 44% of these trials contained at least some flawed data: impossible statistics, incorrect calculations or duplicated numbers or figures, for instance. And 26% of the papers had problems that were so widespread that the trial was impossible to trust, he judged — either because the authors were incompetent, or because they had faked the data.
Beyond these apparently run-of-the-mill problems, even prestigious journals like Nature aren't safe from manipulation by powerful interests. Anthony Fauci's NIH manipulated the scientists behind an important covid paper. His office pressured them to categorically rule out the possibility that the virus had leaked from a lab. When their paper, 'The Proximal Origin of SARS-CoV-2' came out, many were fooled by the deception, including me. That is, until it came out that the Wuhan Institute of Virology was conducting bioweapons research which was probably the original source of the virus.
None of this is intended to suggest that science itself shouldn't be trusted. But when science is used by powerful interests to support questionable policies, it ceases to be a tool for the betterment of all mankind, and instead becomes a prop in the public theater used by the control regime to trick us into complying with the regime. This was on full display during covid, and we can expect to see comparably corrupted science used to rationalize insane climate policies in the near future.
During the pandemic, we were told that trusting the science meant trusting the experts. And we now know that our top public health expert was literally and directly corrupting a scientific inquiry with global implications. These days, I listen to the experts in the same way as I listen to salespeople. They might have accurate information, but every one of them is working an angle.
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