The answer to your question is, weirdly enough, the same answer to why your optical nerve connects to the front of your retina instead of the back, what would be sensible.

Let’s start with an easy system. A purely chaotic system. Evolution. Then we move on to politics.

In evolution, you have a current state and a change. You exist like you do. Then something changes. You get x-men powers. The change is compared to the previous situation and either found better or worse. Better means, you’re more likely to survive and therefore your offspring, sharing that new trait, are more likely survive, leading to you outbreeding your competitors. Well… won’t be x-men powers, reducible complexity and all, but let’s take a look at the retina. If you assume you had an optical nerve and you suddenly grew a retina, that would be better than not having one. Of course, you want the retina in front of the nerve. But it is random chance. Random if you get a retina at all and where you get it. And if it grows behind the nerve, then it will still improve your survivability and you keep it. Again, simplified. There would not be an optical nerve lacking any retina or so, but it just demonstrates randomness and comparing to the previous version.

The idea is, you will always compare a state to a previous state, deem it better or worse, and revert if worse. That has a glaring problem. Evolution has that problem. Machine learning has that problem. The problem is called local optima.

A local optimum is a point in which you’re at the top, meaning, every step you take would make it worse. However, it is not guaranteed to be the best overall point. Imagine a mountain climber on the top of a mountain. He looks in the distance and sees a mountain far higher than the mountain he is on. However, since he always compares his next step with his previous, he can never reach it. Because he has to go down first and his goal is going up. He is trapped on the smaller mountain as long as he is not willing to lose altitude.

Now, politics: Democracies are really bad… I mean for this regression problem. Because, they are very much evolutionary. But the same problem, to a lesser degree, can be found in all other forms of government. Let’s start with an opinion. Assume there are opinions that sound half-way reasonable. Then it is likely that they will have supporters. If the supporters find a majority is almost random. That’s why you can bet at the outcome of elections. We have our random mutation. These supporters will then introduce a change. That change is done and it will either improve or make things worse. If it improves things, everyone is happy. If not, people will change their opinion and vote for someone else next time. And as if that randomness is not bad enough, there is more. Sometimes laws are amended by the opposition. They have a different idea. Sometimes laws are introduced by different parties during the course of many legislation periods with different philosophies. And sometimes parties support ideas or oppose them not because they care, but they care about a completely different issue and try to apply some leverage on those issues. And have I forgotten to mention that sometimes politicians will amend laws because it looks good on the portfolio of a young politician when they successfully have passed an amendment?

All governed by these very important local optima. In machine learning, you solve a local optima problem by increasing the step size. For our mountain climber that means, instead of checking every step if he is higher up than before, he checks every ten steps, or 100 or 20km. That would allow him to jump from one mountain to another. However, that will still end up in a local optimum. After all, he might find the highest mountain top in the rocky mountains, but that won’t allow him to eventually end up on the Mount Everest.

Fun fact, step size in politics could be classified as the form of governance. Democracies have a small step size. Dictatorships a far larger, because the check is done by people getting unhappy.

Anyway, now that we have a grasp of the whole system, we can finally answer why two different reasons are used for citizenship and counting as humans. And the answer, as unsatisfying and simple as it is: Understanding the system, how would you ever come to the idea that there is a logic red line through the system on which laws are made? Instead, the logic red line is simply: “Does it work?” The rest is pretty much random. Like the retina of humans being connected to the optical nerve from the front, the same way in politics, a working solution was found from the realm of working solutions quite randomly and an overall logic is not to be expected.

Jellyfin FOSS

Github with GPL-2.0. So I guess yea, it is. I used Kodi in the past. But had major issues with the jellyfin plugin. I wouldn’t want to do that again.

dolby vision support? both profiles? I didn’t even know what it was until 10 seconds ago… Well, I don’t think I need that.