There is a consistent misperception that experimental and observational support for the EU does not exist. Yet, plasma physics is quite an advanced science at this point, plasma scaling is a known phenomenon distinct from the EU, and the EU uses plasma scaling to suggest fundamental physics explanations for enigmas which – despite all of our technology – continue to plague modern astrophysics & cosmology.
There really is an information problem here. I went through this process of learning the EU, and what I found bothered me quite a bit. The process of taking the idea seriously consumed 8 years of my life. And this really raises very serious questions about what we expect a new emergent idea in science to look like. We have a general expectation that we would appreciate the value of an idea if we saw it, but then if you look at the way that people evaluate new ideas in science, what I’ve seen is that they don’t use the proper criteria. People tend to judge new ideas in science based upon their divergence from established theories, and then they apply a non-rational process (known as associative coherence) to reason, for instance, that the scientific community could not have possibly made such a huge error. I’ve studied many hundreds of scientific discourse threads. People tend to get a sense very early on with the EU that to formulate a truly meaningful opinion of this idea, they would have to do an incredible amount of investigation. Our minds exhibit a complex reaction to this realization, which is best described by the work of Nobel laureate Daniel Kahneman. Phil Barden’s book Decoded takes Kahneman’s theory and applies it to marketing. Taken together, these two resources are going to turn out to be incredibly important for the design of scientific discourse systems which keep our conversations rational.
The evidence for the EU is wrapped up in thick jargon …
plasma
critical ionization velocity (CIV)
Marklund convection
the solar corona’s inverse temperature enigma
electric fields
magnetic fields
double layers
HI hydrogen
radio astronomy countour maps
high-velocity clouds
(etc)
So, this raises a very serious question: If people cannot even understand the terms being used to describe the experimental evidence, then what meaning can the evidence have for people?
This is why I advocate for the creation of a knowledge graph as an infrastructure for the evidence & argumentation. Frankly, we have very serious work to be done on the information visualization aspect of scientific discourse. And this is why I’m here: I came here with some appreciation for the design needs for a scientific social network, after already having put 3 years of research into this site. My intent has been from the start to meet web designers.
The problem of scientific discourse today is that there is no path for new ideas which involve questioning our initial hypotheses to emerge today. These ideas are filtered out at the peer review process. They don’t make it into our popular science programs. Science journalists won’t touch them because that risks their scientific contacts. The culture online rejects them because of the current focus upon pseudoscience. The textbooks generally limit their discussions to the conclusions of scientists. The only option at this point is vanity press publication and journals dedicated to such ideas – which, in a general sense, nobody reads.
So, what I am doing is visualizing discourse in ways that have not yet been tried, like this …
And this is not just something that I made up. Concept mapping has been empirically demonstrated to be an effective pedagogical tool, when used properly. This is a very rudimentary prototype, but the more I study this, the more that I see that much of this design can be implemented using scalable vector graphics in HTML5.
If I sent all of that information at you in pure text, you would immediately lose interest. The switch to a graphical format is much easier on the eyes, and sets into motion a completely different, more constructive set of subconscious reactions.
So, what is really important to do here is to not over-focus upon whether or not the EU and other fringe ideas are actually supported by evidence. The first step to making that evaluation is to build systems which permit us to talk about science in ways which support the emergence of the long tail in scientific discourse. Then, once we have a path for emergence in science, we can then focus upon a visualization approach to moderation. We want the best, most scientific arguments to percolate to the top of the visualization. Accordingly, concept mapping and a new system for rating contributions tend to go hand-in-hand. There is no need to censor views in science. We can simply apply scientific standards to mediate which contributions are most visible. But, the key here is to not let ideological preferences interfere with this process at the level of worldviews. When we are clashing worldviews, we are bound to being agnostic on the worldview if our goal is to create a path for innovative ideas in science to emerge.
There is a risk that by taking a very traditionalist approach to scientific discourse, that we will fail to utilize the technologies which are now at our disposal for sifting through information. The genuine opportunities for a scientific social network are actually quite significant at this point for the very reason that everybody is so focused upon simplistic filters in discourse that dichotomize everything as either science or pseudoscience. We have all of these standards for rating ideas in science today – philosophy of science, Mertonian norms (the “scientific attitude”) and critical thinking standards for identifying biases, are the three primary types. The fact that people still consider thumbs up and down on Slashdot to be some sort of innovation is really kind of laughable. That’s 2,000-year-old “technology” at this point. Most know it as mob rules, and it should be clear by now that mobs oftentimes make mistakes. We can do much, much better than thumbs up and down.
