I like to view it this way: optimal decisions are not computable in practice. We never have enough data, nor enough time, nor is our brain particularly well-suited for this. We have no choice but to approximate, to use heuristics. This applies to both snap decisions and carefully applied formal models. The problem is, even the most rational of us sometimes forget they're just approximating, fudging both data and models at the edges, in order to get some result in finite time. They also forget to mention this.

The difference I see between what I wrote above and what you described as not rational choice of a framework is that, per my personal experience, it is possible to reconcile two conflicting seemingly rational frameworks. It just takes time to extend them past their edges until they meet. That is, extend each past the approximation cut-off point.

You've only created a new rational framework that you have irrationally chosen to use

It’s a little like the newcomb’s paradox. IMO the “rational” action is the one where given the circumstances you win. At least I’d one box in that problem every time given the way it works. In this example, it’s picking up the $100.

The efficient market hypothesis always confused me since it seems empirically false. Who is making the trades that make the market efficient in the first place? Plus people (even large groups of them) are often wrong. Startups and the massive value they can create are an example of that.

Markets are a prediction of predictions to some extent and people are far from agents that act only on hard numbers (and they’re often not wrong to do so). Markets are probably the best tool we’ve got for this, but they’re far from perfectly efficient.