The reason these small sample sizes are used is that with decent sample sizes you would not find all those effects that allow you to publish a lot. That is the whole problem.

The method does, but most scientists do not, as they routinely oversell their results and challenges could actually endanger their funding or reputation. If we were to select professors and researchers actually on scientific merit, and not on "best show provided", things may be different. But today doing good science is a sure way to not be able to work as a researcher beyond a PhD, and even finishing that PhD can be tricky, as you will not publish enough. The system is completely borked because the wrong people have been promoted for a long, long time.

We are well advanced on that path....

Not only measurements. There is a lot of defective CS research being published in all CS fields. "Good" conferences have the additional disadvantage that the trash submitted there is harder to spot, as it is well written trash.

Very much this. The assumption is that papers only cite good research, but is something is really off, I have personally cited papers saying that the people that wrote it have no clue (with evidence of course). I have very rarely seen it done by other authors though, but that may be due to my field (CS).

The other thing is that if you do good research and explore interesting side-aspects, you are never getting a permanent academic position. Those go exclusively to people with a lot of publications (which is a bad sign in itself...). The system promotes bad scientists into positions where they can do and supervise more bad science. It is really a complete mess. And I do understand why so many industrial CS people have an utter disdain for published research, most of it is just so terribly bad it is staggering. To make matters worse, much of these terribly bad publications look good on the surface as that is required to get them accepted. But I have found outright fraudulent publications at Tier-1 conferences, misleading ones and ones that claimed findings without any proof whatsoever. I also know several people that should have their PhD removed, because they did not have the results they claimed they had. They were just clever enough to publish in a venue where the reviewers were impressed by the names on the paper or the writing, but failed to spot the often subtle but critical errors. (No, anonymous review does not help. People that want to benefit from the names of their advisors just publish a technical report that is the same as the paper and make sure Google finds it. Many reviewers even at first-rate conferences are too lazy to do a real review and instead first check whether they can identify the authors and just decides on the names if they are successful.)

Aehm, you did it to yourself?

What probably can be generalized is that only a minority refuses clearly unethical (some may say evil) orders from authority, as long as there is at least some, with Milgram not very large, force behind these orders.

Probably one of the reasons totalitarianism raises its ugly head time and again (and it is well on its way in the west this time): There are just too many participants that can be recruited with minimal effort and they tend to pile up. Humans are mostly still cavemen.

Your fact happens to be bunk because it ignores necessary details. Sure, Biology, Sociology, Gender Studies, Architecture and such often have more women, but that does not make a real-world "50% in the sciences". For example in architecture, I just recently talked to a PhD Construction Engineer (female, and not bad looking either) and she said that her reason to switch over from Architecture after a few weeks were all the very "special" women in there. (She did not say "stupid", but it was strongly implied.) What you find when you actually look is that the "50% women in sciences" (where they exist) are in soft subjects or subjects where a soft path exists and mostly/completely nonscientific subjects (gender studies, education "sciences", etc.) and really, that does not count. Show me some country where female EEs, computer scientists, Physicists, Mathematicians, etc. make 50% of the students, and we can talk again. (Yes, I know some women in all of these disciplines, several of them with PhDs. They do exist. But they are a minority and will remain so.)

Same here. These "studies" often are not much more than the condensed prejudices of their authors. The better ones at least usually only tricked themselves by faulty methodology.

Seriously, you do not think women have free will and think manipulating them into something they do not want to do just to fix a statistic is acceptable?

Or garbage-disposal persons and sewer-cleaners. It is high time this blatantly sexist imbalance gets addressed.