An interactive blogpost by Kevin Simler on network dynamics, with a final section on academia and intellectual progress. I generally think careful exploration of small-scale simulations like this can help quite well with understanding difficult topics, and this post seems like a quite good execution of that approach.
Also some interesting comments on intellectual progress and academia (though I recommend reading the whole post):
For years I’ve been fairly dismissive of academia. A short stint as a PhD student left a bad taste in my mouth. But now, when I step back and think about it (and abstract away all my personal issues), I have to conclude that academia is still extremelyimportant.
Academic social networks (e.g., scientific research communities) are some of the most refined and valuable structures our civilization has produced. Nowhere have we amassed a greater concentration of specialists focused full-time on knowledge production. Nowhere have people developed a greater ability to understand and critique each other’s ideas. This is the beating heart of progress. It’s in these networks that the fire of the Enlightenment burns hottest.
But we can’t take progress for granted. If the reproducibility crisis has taught us anything, it’s that science can have systemic problems. And one way to look at those problems is network degradation.
Suppose we distinguish two ways of practicing science: Real Science vs. careerist science. Real Science is whatever habits and practices reliably produce knowledge. It’s motivated by curiosity and characterized by honesty. (Feynman: “I just have to understand the world, you see.”) Careerist science, in contrast, is motivated by professional ambition, and characterized by playing politics and taking scientific shortcuts. It may look and act like science, but it doesn’t produce reliable knowledge.
(Yes this is an exaggerated dichotomy. It’s a thought exercise. Bear with me.)
Point is, when careerists take up space in a Real Science research community, they gum up the works. They angle to promote themselves while the rest of the community is trying to learn and share what’s true. Instead of striving for clarity, they complicate and obfuscate in order to sound more impressive. They engage in (what Harry Frankfurt might call) scientific bullshit. And consequently, we might model them as dead nodes, immune to the good-faith information exchanges necessary for the growth of knowledge: