Otherwise there is no reason for them. Just look at military aircraft. Incidentally, the same is true for the forward-facing seats. Backwards-facing is better safety-wise, but there are too many people that cannot take that.

"Templates" and "frameworks" are BS and not helping at all. Without them, the bad programmers would be fired pretty quickly, because they could not even get things to run. With them, they can hide for potentially a long time and do untold damage.

And no, I am not trolling in the least. I am deadly serious. I mean, have you looked at the pathetic state of software compared to other engineering disciplines?

I would welcome more women in CS, as long as these are not "quota women" (that are given easier examinations as happens in some places these days). When I did my PhD, we always has some competent women there (about 1:5) and while it does not add on the scientific side (they are just as smart as the men and do not think in any relevant way differently), it does add on the social side. For example, this mix resulted in two, now married, couples and it decidedly produces a nicer atmosphere on any social activity, and may that be just a coffee-break. And on the pure scientific side, while I have yet do discover any different "female" scientific mind-set or way of thinking, even if it is just 20% more scientists, it is 20% more ideas, interesting people, etc. and it would be really stupid to lose them.

But in the other side, I just do not see any evidence (and the women in CS I know did neither) that women are actively prevented from entering the field. I did however hear from several of these women engineers and scientists that "the ladies do not want to work hard" was their personal explanation for the disparity in numbers, usually with expressions of significant disdain and concrete cases to give as example.

I hear McDonalds is hiring. When these people do code, they destroy value created by others as they have negative productivity.

Do you even begin to understand how useless "tech managers" and "teachers" are here? "Tech managers" want "deadline met" above everything else and often have no clue how to recognize bad code. "Teachers" often do not have the first clue how to do things right as they frequently have no practical experience.

And for the record, "passion" does not mean "big ego". Passion means wanting to understand how to do it right and then wanting to do it right. That does decidedly not include "smart" code (that nobody can read), documentation that assumes genius-level readers (after all nobody else is worthy) and defective or insufficient test-cases (after all, the coder is next to God and does not make mistakes...). Yes, I have experience with all these cretins that usually produce code that can only be indented six feed downwards and covered with dirt.

Really, you have no clue how fundamentally broken the "peer review" process is these days. Even if the conference TPC or journal editor is honest, it fails regularly. With a corrupted chair or editor, any old BS can be published by careful peer "reviewer" selection. Yes, I have seen it happen. Yes, I know people that got their PhD by outright publication-fraud. Yes, these were big-name universities involved. And no, there is no working process to complain or out these people.

Actually, that unfortunately is often how science works. I have been contacted numerous times by conference chairs and journal editors, because I was the only peer-reviewer that rejected a paper. None of these was ever published, my arguments were always convincing. Yet the 2-4 other reviewers accepted the things, often just with a "weak accept", but still. Some of these were outright fabrication.

Of course, if you actually have a good idea, the opposite happens: Most reviewers reject your paper. The thing is that most "scientists" are pretty stupid and just follow what is accepted in the mainstream at that time. But if you put in the right buzzwords and fake your results convincingly, it is easy to get published.

And yes, that unfortunately is how science works these days.

And there you confirm your ignorance about how statistics work. You should look up the "Dunning-Kruger Effect" at some time, you are a prime example.

Indeed. I know two women that went the route of system administrator before getting a CS masters and one of them then getting a PhD (doing hardcore statistical data analysis).

Really, are you stupid? Things like these are established facts, you can read up on them. In this case, the info came from her, incidentally, and I was not aware of that fact at the time.

No, actually, it was 13/480 beginners. At least one of the 13 initial women dropped out due to gross incompetence (I knew her). No idea about the others.

Apparently you failed that statistics course. To disprove a hypothesis, you need a much smaller sample. Also, this is not my only data, just the one easiest described.

No, I claim that my sample is large enough that if any of these "studies" were actually accurate, several of my sample would have encountered the effect. They did not.