Despite other suggestions, I encourage you to read the whole book, not just the first chapters. It will give you a very solid understanding of theoretical probability theory, on things like "why the normal", group symmetry priors, nonconglomerability, A_p distributions, etc.

On the other hand, when you have read the first 6 chapters of Jaynes, go look at the first part of Sivia, you'll see Jaynes' concepts laid out with more simpler examples and a high degree of clarity.

The second part of Sivia and the Gelman/Carlin/Stern/Rubin could be used to gain a deeper understanding of what modern probabilistic models actually are and how they are used in practice.
Be aware though, after Jaynes, tolerating the sloppy thinking that is endemic in the field would be much harder.