I am not sure about this, but it seems to me that the electricity explanation starts to win more clearly when you do multiple experiments. (Also, "simplicity of the explanation" is in the mind, because it means the amount of information in addition to what you already know.)
If you would already know everything about laws of physics, then "magic" would be an implausible explanation; the magical toaster would require you to change your model of the world, and that would be too much work. But let's suppose you know nothing about physics; you are just a poorly educated person with a toaster in your hands. At that moment "magic" may be a better explanation than "electricity"...
But then you do multiple experiments. What happens if you put inside a thicker or a thinner slice of bread? Something other than bread? What if you unplug the toaster? The more experiments you do, the more complicated becomes the "magic" explanation, because it must explain why the magic stops working when the toaster is unplugged, etc. (Remember, we are trying to find the simplest explanation that fits the data. A simple wrong model may perfectly fit one data point, but when you have tons of data, the complexity of your model must approach the complexity of the territory.) At some moment, it becomes easier to say "electricity" than to say "magic (which works exactly as the electricity would do)".
I am surprised I didn't say this earlier; I would use the phrase, "most explainable" instead of the phrase, "most simple" to be more fitting to Occam.
This essay claims to refute a popularized understanding of Occam's Razor that I myself adhere to. It is confusing me, since I hold this belief at a very deep level that it's difficult for me to examine. Does anyone see any problems in its argument, or does it seem compelling? I specifically feel as though it might be summarizing the relevant Machine Learning research badly, but I'm not very familiar with the field. It also might be failing to give any credit to simplicity as a general heuristic when simplicity succeeds in a specific field, and it's unclear whether such credit would be justified. Finally, my intuition is that situations in nature where there is a steady bias towards growing complexity are more common than the author claims, and that such tendencies are stronger for longer. However, for all of this, I have no clear evidence to back up the ideas in my head, just vague notions that are difficult to examine. I'd appreciate someone else's perspective on this, as mine seems to be distorted.
Essay: http://bruce.edmonds.name/sinti/