Yes, correct, it prevents the distribution of. Private modifications are fine either way.

The GPL doesn't force you to give the software away. You can sell it. Indeed, RMS himself used to **sell** tapes of GPL software to fund the FSF. RedHat make *billions* on per-seat licensing of GPL software. Nor does GPL software force you, as an author, to GPL all the software. As the author you are completely free to draw the line as you wish between which bits of your software are GPL and which proprietary. You just grant yourself an exception.

What the GPL *does* do, which a BSD licence does not, is protect you from anyone who tries to take your source and then make their own proprietary modificaitions. If you released your code as GPL you can now sue them, and get damages. If you released as BSD, you can't - they are free to make closed modifications to your code (as Apple have done with FreeBSD).

You're at odds with RMS, congratulations, but you're also falling quite a bit short in your understanding of the licences you do and don't have issues with.

Actually, the USA imprisons *more* people - in *absolute* terms - than China, despite China having several multiples the population. The USA leads the world both in terms of absolute prison population and per-capita incarceration rates. Thus, if you want to measure liberty and freedom in their most literal senses, the USA is the worst country in the world. The average Chinese person has a far better chance of NOT being locked up by their government than the average American. (On the other hand the average Chinese person has a much higher chance of being executed).

That's not true. Just recently in the UK a murderer had 1 charge completely thrown out because the arresting officer didn't read him his rights. The murdered confessed and had led the officer right to the body, all ruled inadmissible because the detective decided not to interrupt the murdered while he was confessing. (Luckily there was another murder which he could be convicted on).

StrongARM? Didn't intel sell that to Marvel years ago?

BBC News is pretty simplistic too. It's good for getting a broad overview, but if there's any story you're interested in you'll almost certainly have to go somewhere else if you want to get actual detail. Channel 4 news are better at detail, but sometimes prone to over editorialising.

You appear to be correct, judging by the information in the patch (e.g. see the LWN link posted by someone else, later in these comments). (commenting mostly because I accidently modded you as 'troll' when I'd meant to click 'informative' and this is the only way to undo that).

Single speed mountain biking? You must have thunder thighs :). Nice pink helmet too. ;)

Hi,

The scientology story censored comment story you mention. In CmdrTaco's post on the story, he links to the censored comment, saying its text was replaced. However, that link is broken. This makes me wonder if there's some deeper problem with links in old /. stories?

Oh control for by adding dimensions to the data as necessary to deal with that - not dropping the data!

Of course there are. The statistics most people do is 2-variable, but statistics generalises perfectly well to multiple variables. The quality of a study may need a subjective assessment, but you can assign it a value and it becomes another dimension to your data, then find out how it correlates with other dimensions in your data. Some of the stuff I do on finding hidden structure in large, complex graphs/networks uses techniques that also are used in multi-variate statistical analyses.

I agree there may be a need to filter for medical treatment studies. I agree pharmaceuticals have manipulated the public record (from which meta-studies must draw) with poor studies. However, they have also manipulated the public record by _withholding_ studies from the public record. (By co-incidence I'm reading Ben Goldacre's "Bad Pharma" at the moment, which takes issue with that withholding trick and its distorting effect - very interesting book so far).

One of the problems with judging helmet efficacy of course is that it is *very* hard to do well controlled studies. intrinsically, if we want statistics that measure real-world efficacy of helmets, we're going to have to work with extremely noisy signals. The best way to deal with noise is to use as much data as possible (and control for the differences in methodologies).

BTW: The limited-time period trick has been used by studies that found helmets had a large positive effect too. ;)

I'm using bias in a non-pejorative, technical, statistical sense. Clearly either: a) There is some underlying bias why studies where helmets were less effective were also less likely to meet Thompson's Cochrane review standards OR b) There is a bias in the Cochrane review OR c) There is a "biased" co-incidence (random chance that creates a pattern that looks like bias).

FWIW, I have both studies open. They both have good discussions on this. I think we'd both be better off just reading them and deciding from that. I'm sticking to my belief that bias is best dealt with by gathering and aggregating more data and using mathematical tools to deal with any differences in methodology and results, rather than using more subjective "quality" criteria to exclude data-points.

One thing, the Elvik meta-study a different data-set to the Thompson Cochrane Collab. paper, which is interesting. The Elvik paper is updating a 2001 meta-study, Attewell, with new data-points. The Cochrane paper uses some of the same, and additional ones. There are primary-papers in the Attewell study though which the Thompson paper did not find at all - even though it found the Attewell meta-study. Similarly there are primary-papers in the Thompson paper, which pre-date Attewell significantly, but which Attewell does not mention. This makes me think the search strategy in both those meta-studies might have been sub-optimal - unless there's some important factor I've missed. If I havn't missed anything, it'd be interesting to see a meta-study with search criteria that caught at least all the primary works in those meta-studies.

Also worth noting is that several of the studies excluded from the Thompson paper were published in Accident Analysis & Prevention, as was the Attewell meta-study.

Oh, I'm not arguing for apples-oranges comparisons. There are objective, mathematical methods to deal with multi-variate results, rather than just excluding ones you don't like.

I don't have expertise in or much knowledge of the medical world, but my mathematical knowledge is not comfortable with "less is more" wrt statistical analysis. The answer to noise is to aggregate over more data, not have humans apply their judgement as to which signals are and are not representative. That path is certain to result in misleading conclusions at times, even with the best intentions from the best experts.

Gah, correction: A result aligned bias that is, so more likely to be systematic, less likely to be random co-incidence.