Many biases have their start in the biases hidden within the constraints of science


The theories we believe we call facts, and the facts we disbelieve we call theories 

Felix Cohen - US lawyer & philosopher



When we watch a TV documentary about a scientific topic, or read a news report about the latest scientific discovery, we accept the information is reliable and that the work was carried out in accordance with the highest traditions of human thinking: "The Scientific Method".  We know history has revealed a few scientific mistakes, even less frauds, and we also know scientific ideas improve as knowledge increases; but in general we accept the intrinsic quality of the scientific output.  But is this assessment correct or should bias be considered? 


The first question that must be asked is: what is the scientific method? It seems experts who give opinions in many textbooks, and on the internet, are confident the scientific method can be summed up with a single straightforward definition, something like the straightforward graphic above here.


But a few moment's thought suggests this may not be the full story. We see that some studies use fully controlled laboratory experiments, while many must be satisfied with tests that are less controlled, and others carry out some work away from a laboratory or just observe existent conditions. Some sciences seek to discover natural laws; others classify and organize natural objects; yet others reconstruct past events (that`s what forensic engineers and scientists do). Further, we see some sciences test their theories by making predictions while others attempt to assess their explanatory power. Some methods involve direct verification; others use indirect methods. Some test in isolation of any competing theory; others test comparatively; even others provide no way of testing. Finally, some sciences use direct observations, others use proxies to create data and evidence, and many "observe" by making one or more inferences based upon their effects. Finally, some sciences use mathematics to describe observed events, others use math(s) to describe events that have not, or cannot, be observed, and many provide little in the way of mathematical support.*  


In addition to these various procedural differences, there are hundreds of specialties within the world of science. There are many millions of scientists worldwide each with different skills and talents so it would not be surprising if methods and standards varied. Also, to quote comedian Jerry Seinfeld when talking about the quality of doctors: Someone is graduating at the bottom of the class.


The outcome of these different methods working side-by-side has caused cracks to appear in the monolithic façade of science. In numerous fields of study there is a growing list of warning signs. Scientific anomalies – those pesky data points that fail to fit in with the majority - rather than being resolved, appear to be increasing; many findings cannot be reproduced by other researchers; and there is a rapid about face in many conclusions.


Some in the scientific establishment do recognize these problems but there is no consensus on how the quality control procedures should be improved. 


So how do we make sense of all this? This analysis is not a criticism of science, it is a clarion call for both scientists and consumers to upgrade their scientific literacy. The work presented in this site suggests this can be done by focusing on the potential for bias, and the human assumptions that scientists make. This approach would require scientific work to be divided into categories. As a minimum two are suggested - Foundational and Complex – but better yet they could be subdivided into a number of distinct classifications, each with their own clear-cut procedures.


* Based upon an idea by Dr. Stephen C. Meyer.

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