2y of data. They should address that confounder and demonstrate the results are stable even if you stratify over time. 2026 models are very different from 2024 ones, after all.
I really liked the main question. But I’m more interested in the structure how we journal, not if you use Logseq, OrgMode, paperback, etc.
For example, I try to journal by treating my work as “experiments” and tie those in turn to goals and challenges. And my experiments consist of a plan, prediction, the actual data, and the evaluation (of the data against the prediction). Finally, I constantly track the current state relevant towards the goal. If that sounds familiar to the Toyota Kata, that is because it is. And it should sound familiar to anyone trying to apply the scientific method.
Here’s another example: Apple Arcade decided to discontinue my kids’ favorite local multiplayer game (Marble Knights). Apple erased the game from my devices and there is no way to get this game at all now, at least as far as I know. With the pending increase in Arcade’s monthly costs, that was the last straw for me to say goodbye to this Apple “offering”.
The problem with maximizing efficiency is that it kills diversity and creativity. In my home country, Austria, everyone can study anything for free, and I think it has not had that negative impact either. Most people are reasonable and will study something they can make a living off.