While Going through 2 papers by the author /co-author these papers it struck me much later than it should have that the paper I will next post on, empirical forecasting, is in in principle intrinsically linked to the case made by the authors against the weighting of scientific consensus in terms of credence given to the argument in question. Despite this I will post them seperately and include the link later. The reasoning, accuracy and absence of intractable logical conflicts really should be the the basis on which any published paper or scientific hypotheses is based. The filtering process should never become greater than the idea. That sort of thinking is for small minded bureaucrats and really has no place in the arena of scientific ideas.
When I first started writing this blog I wrote about this topic, here is that post:
An Audio of my old blog post above.
It was a broadly cast and "all over the place" post yet I don't regret a word of it. That being said I didn't know a heck of a lot on the topic back then and I would like to make this paper, a more methodical and structured deconstruction of the issue, much more rigerous than I could ever do, available to myself to posterity to refer back to.
To anyone reading this, I hope you enjoy it as much as as I did.
CONSENSUS IN SCIENCE
by Peter Stallinga and Igor Khmelinskii
Consensus in science
ABSTRACT
The biggest argument in some areas of science is the existence of a consensus. However, on top of it being a non-scientific argument, it is easy to show how a consensus naturally evolves in modern research environments. In this paper we demonstrate analytically and by cellular automata how a consensus is obtained. Important conclusions are that a consensus is not necessarily representing the truth and, once established, can never change anymore.
Read more here and purchase the article for €30.00
Or read the text images below which I have made screenshots of at no cost.
