Let’s start with the truth.

About
The Broken Science Initiative

Watch Video
"If fallacious reasoning always led to absurd conclusions, it would be found out at once and corrected. But once an easy, shortcut mode of reasoning has led to a few correct results, almost everybody accepts it; those who try to warn against it are not listened to."
E.T. Jaynes

Probability Theory: The Logic of Science

"What the use of P [the significance level] implies, therefore, is that a hypothesis that may be true may be rejected because it has not predicted observable results that have not occurred."
"Perhaps the most important function of the demarcation between science and nonscience is to refuse political and religious authorities the right to pass binding judgments on the truth of certain statements of fact."
/

Consensus has replaced predictive value in academic science, definitions have become subjective and replication is no longer a requirement. The BSI will help anyone interested identify and object to this tyranny of bad science. The remedy to broken science will only be found when Popper, Kuhn Feyerabend, Lakatos, Fisher and others are dethroned and replaced with Laplace, Jefferys, Shannon, Cox and Jaynes. Dating back to 1814, when Pierre-Simon Laplace penned Essai philosophique sur les probabilités, establishing the system of inductive reasoning we know today as Bayesian, up to the present day statistician Matthew Briggs, working scientists have tried to alert the masses to the necessity of predictive power in science. Yet, they were largely ignored. The Establishment prioritized the philosophers’ views on science–which lacked a definition, found significance when there wasn’t any and was far more corruptible, over the approach of actual scientists in the trenches. The Broken Science Initiative will show any person interested that it’s time for a new pantheon and a renaissance that requires predictive power in science. 

Modern science is source and repository of man’s objective knowledge. Scientific knowledge is siloed in models. A model maps a fact to a future unrealized fact as a prediction. A fact is a measurement. A measurement is an observation tied to a scale with an expressed error. An observation is a registration of the real world on our senses or sensing equipment.

Join BSI

Becoming a member gives you access to exclusive content and discussion forums.

Verified by MonsterInsights