Over the years, we’ve seen that much of today’s “science” is corrupt. Climate “science” for example, is often climate cultism, with scientists retrofitting data to reach predetermined conclusions. When it came to COVID and the vaccine, profit seemed to be the main driver, along with some scary WEF theories, including some people believing that the real purpose behind the dishonest rush to force vaccines on people is tied to “transhumanism” and depopulation, both of which are values the WEF crowd promotes. Now, there’s even more evidence about the utter unreliability of modern science.

Science is not a god. It is, instead, an approach to processing and analyzing data. In a perfect world, one has a theory to which one applies a very strict methodology and, from that, achieves a reliable result. Livescience offers as good an explanation as any:

Every scientific theory relies on the scientific method. A scientist may make an observation and devise a hypothesis to explain that observation, then design an experiment to test that hypothesis. If the hypothesis is shown to be incorrect, the scientist will develop a new hypothesis and begin the process again. If the hypothesis is supported by the results of the experiment, it will go on to be tested again. If the hypothesis isn't disproven or surpassed by a better explanation, the scientist may incorporate it into a larger theory that helps to explain the observed phenomenon and relates it to other phenomena, according to the Field Museum.

A scientific theory is not the end result of the scientific method; theories can be proven or rejected, just like hypotheses. And theories are continually improved or modified as more information is gathered, so that the accuracy of the prediction becomes greater over time.

This approach promises to bypass human biases in favor of a level of objectivity that allows us to understand some ultimate truths about the natural world. But then, leftists got hold of science. That first happened in the Soviet Union with Lysenkoism. Soviet biologist Trofim Lysenko, under the umbrella of science, promoted anti-science for political purposes:

More than 3,000 mainstream biologists were dismissed or imprisoned, and numerous scientists were executed in the Soviet campaign to suppress scientific opponents. The president of the Soviet Agriculture Academy, Nikolai Vavilov, who had been Lysenko's mentor, but later denounced him, was sent to prison and died there, while Soviet genetics research was effectively destroyed. Research and teaching in the fields of neurophysiology, cell biology, and many other biological disciplines were harmed or banned.

If that sounds like what’s been happening in the realm of climate “science,” gender “science,” and COVID “science,” you’re right. We haven’t yet got to the point of imprisonment and executions in America, but they’ve already been arresting people in other parts of the world for deviating from the COVID “science.” In America, they’re just taking away people’s livelihoods if they dare to challenge vaccines.

However, it’s not only ideology or funding leading to unreliable “scientific” conclusions. Instead, it turns out that the choices a scientist makes about handling data will also affect the outcome, sometimes in quite dramatic ways:

In a massive exercise to examine reproducibility, more than 200 biologists analysed the same sets of ecological data — and got widely divergent results. The first sweeping study¹ of its kind in ecology demonstrates how much results in the field can vary, not because of differences in the environment, but because of scientists’ analytical choices.

For that reason, the study’s authors suggest that nothing should be relied upon unless many different studies lead to the same conclusion. To prove how important multiple studies are, they asked almost 250 biologists to create studies using identical data sets:

The study by Fraser and her colleagues brings the many-analyst method to ecology. The researchers gave scientist-participants one of two data sets and an accompanying research question: either “To what extent is the growth of nestling blue tits (Cyanistes caeruleus) influenced by competition with siblings?” or “How does grass cover influence Eucalyptus spp. seedling recruitment?”

Most participants who examined the blue-tit data found that sibling competition negatively affects nestling growth. But they disagreed substantially on the size of the effect.

When the authors had those varying conclusions peer-reviewed, the peer review process wasn’t any more reliable.

The logical conclusion at this point, of course, is to question the study described above. (Rim shot!) However, if we abandon science in favor of common sense, it makes sense that, if we’re planning to abandon all prior knowledge in favor of something new, we’d better stop and do another study, and another, and another, and another. As we’ve learned to our cost over the last few decades, corrupt science is just another form of tyranny, and it needs to be stopped before it can take root.

UPDATE: Arnold Cusmariu added this important point:

As this essay explains, there is a basic difference between the hard sciences (physics & chemistry) and the not-so-hard sciences (biology). It's important to be careful and not lump them together as you do in your blog. Briefly, the hard sciences rely on laws of nature, which are in ODE form (ordinary differential equation, Newton) or PDE form (partial differential equation, Maxwell). Neither kind exists in biology. The fact that biology is messy is not a reflection on real science, i.e., physics and chemistry. The climate-change stuff is just plain garbage. Shame on physics for not saying that.

Image: Scientist by DCStudio.