It's like how a real terrorist would not joke about a bomb at an airport. But someone who does is detained or arrested, and time is spent by TSA that could be better spent looking for real terrorists.
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I studied and tutored experimental design and this use of inferential statistics. I even came up with a formula for 1/5 the calculator keystrokes when learning to calculate the p-value manually. Take the standard deviation and mean for each group, then calculate the standard deviation of these means (how different the groups are) divided by the mean of these standard deviations (how wide the groups of data are) and multiply by the square root of n (sample size for each group). But that's off the point. We had 5 papers in our class for psychology majors (I almost graduated in that instead of engineering) that discussed why controlled experiments (using the p-value) should not be published. In each case my knee-jerk reaction was that they didn't like math or didn't understand math and just wanted to 'suppose' answers. But each article attacked the math abuse, by proficient academics at universities who did this sort of research. I came around too. The math is established for random environments but the scientists control every bit of the environment, not to get better results but to detect thing so tiny that they really don't matter. The math lets them misuse the word 'significant' as though there is a strong connection between cause and effect. Yet every environmental restriction (same living arrangements, same diets, same genetic strain of rats, etc) invalidates the result. It's called intrinsic validity (finding it in the experiment) vs. extrinsic validity (applying in real life). You can also find things that are weaker (by the square root of n) by using larger groups. A study can be set up in a way so as to likely find 'something' tiny and get the research prestige, but another study can be set up with different controls that turn out an opposite result. And none apply to real life like reading the results of an entire population living normal lives. You have to study and think quite a while, as I did (even walking the streets around Berkeley to find books on the subject up to 40 years prior) to see that the words "99 percentage significance level" means not a strong effect but more likely one that is so tiny, maybe a part in a million, that you'd never see it in real life.
I've been using Linux for an awfully long time, since the mid 1990s (Yggdrasil, then Debian).
Darn noobs! I remember having fun making the MCC Interim distribution work...
The UK is putting its judicial system under tremendous financial pressure at the moment, to the extent that some criminal cases are just being abandoned because there's insufficient money to run them. They're (finally!) starting to experiment with allowing small claims court cases to be resolved over the phone, and also looking at decriminalising TV license violations to reduce pressure on the system. But you get the idea - the judicial system innovates extremely slowly even when being sliced to the bone. So don't hold your breath.
They're also moving the low-level courts to use a lot more technology to support them, things like video links so remand prisoners do not need to be brought to court, tablet computers with the legal texts on them in searchable form, that sort of thing. These are the sorts of things that technology can definitely help with, even though they definitely change the nature of justice somewhat.
This is one reason the US (which only funds healthcare for Federal employees, Federal retirees, 65-year-olds, and the poor) actually paid more per capita for health care then the Canadian Federal government did, despite the fact that the Canadian Feds provide 100% of health funding in that country.
The real key is that there is a body in Canada (other than the ordinary Joe on the street) who wants prices to be kept down, and which has the power to actually make that happen. Because keeping charges down is a priority, use of generic drugs will be more widespread, as will the use of programmes to improve general public health (because they tend to be very cost effective overall) and the more rapid progression from diagnosis to treatment. That last point can be both good and bad: good because if they got it right, you're getting treated sooner instead of having more expensive (and possibly invasive) tests done, and bad because if they got it wrong, you're not being treated for what's wrong at all.
I haven't heard anybody discuss what the half-life of graphene is though, so it could be just as bad.
They're probably still working that out. It's one thing to know that it's theoretically possible, but another to demonstrate how to actually do it, so the report that it has been done (even if it turns out to not be very useful in the end) is relevant.