This post proposes 4 ideas to help building gears-level models from papers that already passed the standard epistemic check (statistics, incentives):
Look for papers which are very specific and technical, to limit the incentives to overemphasize results and present them in a “saving the world” light.
Focus on data instead of on interpretations.
Read papers on different aspects of the same question/gear
Look for mediating variables/gears to explain multiple results at once
(The second section, “Zombie Theories”, sounds more like epistemic check than gears-level modeling to me)
I didn’t read this post before today, so it’s hard to judge the influence it will have on me. Still, I can already say that the first idea (move away from the goal) is one I had never encountered, and by itself it probably helps a lot in literature search and paper reading. The other three ideas are more obvious to me, but I’m glad that they’re stated somewhere in detail. The examples drawn from biology also definitely help.
This post proposes 4 ideas to help building gears-level models from papers that already passed the standard epistemic check (statistics, incentives):
Look for papers which are very specific and technical, to limit the incentives to overemphasize results and present them in a “saving the world” light.
Focus on data instead of on interpretations.
Read papers on different aspects of the same question/gear
Look for mediating variables/gears to explain multiple results at once
(The second section, “Zombie Theories”, sounds more like epistemic check than gears-level modeling to me)
I didn’t read this post before today, so it’s hard to judge the influence it will have on me. Still, I can already say that the first idea (move away from the goal) is one I had never encountered, and by itself it probably helps a lot in literature search and paper reading. The other three ideas are more obvious to me, but I’m glad that they’re stated somewhere in detail. The examples drawn from biology also definitely help.