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Comment Re:Rural populations mostly vote red (Republican) (Score -1) 62

Just imagine, if you could be taxed more for unproductive infrastructure. Everything in the world would be solved, if you would just pay everything to the government, and they could re-distribute all of your income to others.

The entire reason why industrialization has delivered the promises of socialism, while socialism brought mass scarcity everywhere, is that productive activity generates resources that can be spent elsewhere.

Meanwhile taking more and more from existing industries, only to fund unproductive things (i.e. electric lines that don't allow for more production to offset their costs) improvershes everyone. It's why PRC has as many problems with useless infrastructure they built as they do. It's why their property market collapsed a few years ago.

Comment Re:Rural populations mostly vote red (Republican) (Score -1) 62

Loudoun county is a well known example. There are several others.

https://progresschamber.org/in...

This isn't really new or interesting. If you manage to get a lot of new industry in, you can tax that industry instead of your residents. Meaning you can fund more services, while taking less tax.

Comment Re: Probably due to methodical errors (Score 1) 177

I just looked at the paper and you are right. Thanks for looking.

The male and the female one are basically suggesting visually that the man is competent and the woman is not. I mean even only the cloth pattern of the skirt that "she" is wearing is atrocious. It is like they made the "woman" intentionally unattractive while they made the "man" average. ("She" is also blonde, of course, while "he" has dark hair.) I have no idea whether this was actually done intentionally, but if I were to design a study to find this type of bias, that is what I would use. I wonder whether they did something similar in the text interfaces.

I also noticed that their names are Johanna and Johan, i.e. a proper male name for "him" and a feminized male name for "her".

So, after all, my first take of "likely methodical error" was correct.

Comment Re:you cant be serious. (Score 2) 177

The study is flawed in another way as well because "everybody knows" that women earn less than men. (Usually that is "proven" with the unadjusted wage gap, which is completely bogus and essentially a lie.) Hence the study participants just conformed to what they thought were the facts of the matter. Makes the results completely meaningless.

Comment Re: confirmation bias (Score 2, Insightful) 177

And the other thing is that "everybody knows" there is a gender pay gap. This is only true for the unadjusted gap, but most people do not know what that means. Once you adjust for factors like experience and field-of-work the difference is below the margin of error, i.e. small and we do not even know whether it is real. We essentially have same wages for the same work and qualification and had it for a while. That some parts of some gender groups decide to not do the same work or invest less or more time into getting experience is a separate problem and not a problem of payment.

Hence the people in this "experiment" were just conforming to what they thought was expected of them. That makes the whole thing bogus. Obviously wages in the real world are determined by a different procedure and harping on about women and men not behaving exactly the same (as a group) is just one thing: counterproductive.

Comment Re:mostly mash-ups of existing techniques (Score 1) 106

While they are trained on existing data, they are also capable of reasoning.

No. Or rather not to any meaningful degree or depth. They can do very shallow reasoning only and after a few steps into deeper reasoning chains, only noise is left. Statistical AI is completely unsuitable for automated deduction. It is not even remotely comparable to what a smart human or even the very limited automatic theorem proving systems can do.

Comment Re:Prove it. (Score 1) 45

I am with Roger Penrose on this: Quantum theory is wrong. Saying it is "incomplete" is just a more polite form of saying it is wrong. Now, you do not abandon theories you know are wrong unless you have better ones. But you always remember they are wrong and you are careful not to make sweeping predictions based on them.

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