Coverity: Hey you, proprietary software developer with the deep pockets. Yeah, you. We've got this great tool for finding software defects. You should buy it.
Proprietary software developer: get lost.
Coverity: Hey, open source dudes, we've got this great defect scanner. Want to use it? Free of course!
Open source dudes: Meh, why not?
Coverity: Hey proprietary software developer, did we mention those dirty hippie neck beards are beating the stuffing out of you in defect (that we detect)-free code?
Except that the "impossible" happens every day outside the US. Actually, IIRC, even in the US there are states that frequently have independents, third parties or non-partisan candidates in their legislatures, aren't there? Local governments may be even more diverse.
There seems to be something peculiar about either the US federal system, the American people, or both.
One example? Really? I have no trouble believing that the powers in the US are unhealthily interested in maintaining those powers, but one example (and kind of an iffy one at that) doesn't mean much. It's also irrelevant to the point: the reason there aren't third parties in the US (and the reason the two ruling parties get away with things they shouldn't) is that Americans don't vote for third parties.
True, the US presidency is kind of a strange setup that's not seen much elsewhere, and it's the most extreme possible example of representative voting, where you're electing just one representative.
Most people mean a literal democrat when they refer to it. A democracy is a system in which all eligible citizens participate equally, either directly or through elected representatives.
When the US was founded "democracy" was usually used to mean direct democracy specifically. That's no longer the case.
Duverger's "law" is a "tendency". Whether it's true or not, many democracies around the world demonstrate that it is not necessarily overwhelming. As you point out, it also doesn't mean that one or both of those two parties won't be kicked to the curb.
Most revolutions have failed. Some appear to succeed, but are either quickly subverted or defeated in a counter revolution. The American revolution seems to be one of the few that succeeded and met it's expressed goals at least for a time.
There are a large number of countries (including one just to the north of you Americans) that have strong third (or fourth or fifth) parties and frequent minority or coalition governments. Ruling parties occasionally get slammed so hard in elections they are almost entirely shut out and take years or decades to rebuild.
What you say is true, but it's not a rebuttal of the parent. The reason the US only has two valid parties is that the populace doesn't bother to run alternative candidates, or to vote for them. There are lots of soft factors that have been put in place to discourage it, but there's nothing to prevent a third (or fourth, or fifth) party from gaining power except the will of the people.
Our society recognizes that some people are in trusted positions and need to be held to a higher level of responsibility for their actions as a result. Physicians are sued all the time for giving bad medical advice. That's why they have malpractice insurance. Businessmen, researchers, lawyers, etc, who knowingly lie or are negligent in their professional capacity can also be held responsible. Celebrities who are trusted by a large number of people and insist on giving potentially dangerous advice are no different.
Yes. You should appeal to scientific evidence. Which is entirely on the side of vaccines. While the precise benefit of things like the flu vaccine in non-vulnerable populations isn't always entirely clear, the risks and benefits of standard childhood vaccines are well studied and well known.
No, you shouldn't trust random doctors, whether they're on Oprah or not. And you certainly shouldn't trust random Playboy bunnies, whether they're on Oprah or not.
McCarthy's most important flaws are that she feels the need to give medical advice to millions of people based on absolutely nothing but her own prejudices, which she clings to in the face of overwhelming evidence.
She has made specific claims about vaccines being unsafe. These claims are wrong, yet she's stuck to them. She's also given medical advice to millions of parents based on these demonstrably wrong claims. Regardless of what she claims her philosophical stance is, she's guilty of gross and willful negligence causing multiple deaths.
Peer review isn't meant to assure accuracy. It's a filter to stem the tide of obvious crap. Scientific journals started as letters that scientists wrote to each other. They're the same thing now, except the letters get published centrally. An article in a scientific journal is "hey, look, we did this, and this is what we found."
Wakefield's paper itself seems to be the honest report of a valid experiment. Since he found something that would have important consequences, it was subsequently examined in depth. Nobody could replicate his results. That can happen, because statistical false positives and honest mistakes happen all the time, but further investigation revealed that Wakefield experimented without ethics approval on his son's friends, cherry picked data, purposely misrepresented data, and had a serious undisclosed conflict of interest in owning a share in and consulting for an alternative vaccine company.
The Wakefield thing is how science is supposed to work. The public needs to learn that single articles published in scientific journals aren't necessarily correct. In fact, analysis suggests that most of them are not correct.
You're still making conclusions that aren't based on the data. There's nothing in their project that identifies why individuals, or the group, might be better than the experts, and my question is about whether the individuals they've identified ARE even better than the experts or if they've simply discovered the right side of a Bell curve (a la Niven).
There have been studies that have shown that crowds, under certain circumstances, can be somewhat resistant to bias. In other circumstances this is obviously not the case. Examples include antivaxers, the number of Americans who believe the moon landings were hoaxes and anything featured on Oprah, Dr Oz or Dr Phil. "The wisdom of crowds" is a catchy name for a special case of the observation that the signal to noise ratio increases by the square root of the number of measurements that are averaged. It doesn't have anything to do with bias.
The author of the bug probably introduced it accidentally. It's easy to do. The author of the special wrapper code in openSSL that purposely prevents newer versions of malloc from doing memory checking that would have revealed this bug a little more suspicious.
Expert forecasters also average their perceived probabilities from lots of different sources. There's nothing magic about a small town pharmacist doing it. The summary and a lot of Slashdotters seem to like to play up the anti-expert angle, but it's certainly not relevant to my OP, and I doubt the project has produced any evidence for your conclusion.
Or does it mean the experts were correct 55% of the time and the top guessers, I mean, super-predictors, were right 56.5% of the time? That would be the normal meaning of a percent difference.
You should read the article. There's a little section about "wisdom of crowds" and then the balance of it is about particular people they've selected as being super accurate, such as the pharmacist they use as an example. If you take enough people and ask them to guess randomly, some of their guesses will line up very nicely with the answers to any questions. Purely by luck. If you cherry pick these randomly lucky guessers and don't properly allow for your cherry picking in your calculation of expected performance, you will be misled badly.
A different version of the same phenomenon confuses people who try to write classifiers. I have a friend who was trying to classify patients who did or did not have a disease. He put a bunch of measurements into the classifier, trained it, and look, it was 100% accurate! He was suspicious, so he put in a bunch of randomly generated numbers, trained it, and look, it was 100% accurate! Of course, neither version did any better than chance on data it hadn't been trained on.
In statistics it's called an unbiased estimator. Most people know it as an average. It doesn't have any particular link to crowds and the behaviour is very well defined. It does, however, require that the individual estimates be wrong in a random way.
You managed to pick exactly the same example I did.
Yes, that's what the article says. In a scientific paper that would be in the discussion, possibly in the conclusions. Experienced scientists know that the discussion, and depressingly frequently the conclusions, are BS the authors made up that's not really supported by the data, one way or the other.
Slashdot Mirror
Coverity: Hey you, proprietary software developer with the deep pockets. Yeah, you. We've got this great tool for finding software defects. You should buy it.
Proprietary software developer: get lost.
Coverity: Hey, open source dudes, we've got this great defect scanner. Want to use it? Free of course!
Open source dudes: Meh, why not?
Coverity: Hey proprietary software developer, did we mention those dirty hippie neck beards are beating the stuffing out of you in defect (that we detect)-free code?
PSD: Fine, how much?
Except that the "impossible" happens every day outside the US. Actually, IIRC, even in the US there are states that frequently have independents, third parties or non-partisan candidates in their legislatures, aren't there? Local governments may be even more diverse.
There seems to be something peculiar about either the US federal system, the American people, or both.
It's your cynicism and tendency to wild generalizations with little to no evidence. Also gratuitous capitalization.
One example? Really? I have no trouble believing that the powers in the US are unhealthily interested in maintaining those powers, but one example (and kind of an iffy one at that) doesn't mean much. It's also irrelevant to the point: the reason there aren't third parties in the US (and the reason the two ruling parties get away with things they shouldn't) is that Americans don't vote for third parties.
True, the US presidency is kind of a strange setup that's not seen much elsewhere, and it's the most extreme possible example of representative voting, where you're electing just one representative.
Most people mean a literal democrat when they refer to it. A democracy is a system in which all eligible citizens participate equally, either directly or through elected representatives.
When the US was founded "democracy" was usually used to mean direct democracy specifically. That's no longer the case.
http://en.wikipedia.org/wiki/D...
Duverger's "law" is a "tendency". Whether it's true or not, many democracies around the world demonstrate that it is not necessarily overwhelming. As you point out, it also doesn't mean that one or both of those two parties won't be kicked to the curb.
Most revolutions have failed. Some appear to succeed, but are either quickly subverted or defeated in a counter revolution. The American revolution seems to be one of the few that succeeded and met it's expressed goals at least for a time.
There are a large number of countries (including one just to the north of you Americans) that have strong third (or fourth or fifth) parties and frequent minority or coalition governments. Ruling parties occasionally get slammed so hard in elections they are almost entirely shut out and take years or decades to rebuild.
What you say is true, but it's not a rebuttal of the parent. The reason the US only has two valid parties is that the populace doesn't bother to run alternative candidates, or to vote for them. There are lots of soft factors that have been put in place to discourage it, but there's nothing to prevent a third (or fourth, or fifth) party from gaining power except the will of the people.
Our society recognizes that some people are in trusted positions and need to be held to a higher level of responsibility for their actions as a result. Physicians are sued all the time for giving bad medical advice. That's why they have malpractice insurance. Businessmen, researchers, lawyers, etc, who knowingly lie or are negligent in their professional capacity can also be held responsible. Celebrities who are trusted by a large number of people and insist on giving potentially dangerous advice are no different.
Yes. You should appeal to scientific evidence. Which is entirely on the side of vaccines. While the precise benefit of things like the flu vaccine in non-vulnerable populations isn't always entirely clear, the risks and benefits of standard childhood vaccines are well studied and well known.
No, you shouldn't trust random doctors, whether they're on Oprah or not. And you certainly shouldn't trust random Playboy bunnies, whether they're on Oprah or not.
McCarthy's most important flaws are that she feels the need to give medical advice to millions of people based on absolutely nothing but her own prejudices, which she clings to in the face of overwhelming evidence.
And Oprah made both of them.
She has made specific claims about vaccines being unsafe. These claims are wrong, yet she's stuck to them. She's also given medical advice to millions of parents based on these demonstrably wrong claims. Regardless of what she claims her philosophical stance is, she's guilty of gross and willful negligence causing multiple deaths.
Peer review isn't meant to assure accuracy. It's a filter to stem the tide of obvious crap. Scientific journals started as letters that scientists wrote to each other. They're the same thing now, except the letters get published centrally. An article in a scientific journal is "hey, look, we did this, and this is what we found."
Wakefield's paper itself seems to be the honest report of a valid experiment. Since he found something that would have important consequences, it was subsequently examined in depth. Nobody could replicate his results. That can happen, because statistical false positives and honest mistakes happen all the time, but further investigation revealed that Wakefield experimented without ethics approval on his son's friends, cherry picked data, purposely misrepresented data, and had a serious undisclosed conflict of interest in owning a share in and consulting for an alternative vaccine company.
The Wakefield thing is how science is supposed to work. The public needs to learn that single articles published in scientific journals aren't necessarily correct. In fact, analysis suggests that most of them are not correct.
Her Tatas. She's got 'em, and she's been happy to show them off.
You're still making conclusions that aren't based on the data. There's nothing in their project that identifies why individuals, or the group, might be better than the experts, and my question is about whether the individuals they've identified ARE even better than the experts or if they've simply discovered the right side of a Bell curve (a la Niven).
There have been studies that have shown that crowds, under certain circumstances, can be somewhat resistant to bias. In other circumstances this is obviously not the case. Examples include antivaxers, the number of Americans who believe the moon landings were hoaxes and anything featured on Oprah, Dr Oz or Dr Phil. "The wisdom of crowds" is a catchy name for a special case of the observation that the signal to noise ratio increases by the square root of the number of measurements that are averaged. It doesn't have anything to do with bias.
Three years is quick?
The author of the bug probably introduced it accidentally. It's easy to do. The author of the special wrapper code in openSSL that purposely prevents newer versions of malloc from doing memory checking that would have revealed this bug a little more suspicious.
Expert forecasters also average their perceived probabilities from lots of different sources. There's nothing magic about a small town pharmacist doing it. The summary and a lot of Slashdotters seem to like to play up the anti-expert angle, but it's certainly not relevant to my OP, and I doubt the project has produced any evidence for your conclusion.
Or does it mean the experts were correct 55% of the time and the top guessers, I mean, super-predictors, were right 56.5% of the time? That would be the normal meaning of a percent difference.
You should read the article. There's a little section about "wisdom of crowds" and then the balance of it is about particular people they've selected as being super accurate, such as the pharmacist they use as an example. If you take enough people and ask them to guess randomly, some of their guesses will line up very nicely with the answers to any questions. Purely by luck. If you cherry pick these randomly lucky guessers and don't properly allow for your cherry picking in your calculation of expected performance, you will be misled badly.
A different version of the same phenomenon confuses people who try to write classifiers. I have a friend who was trying to classify patients who did or did not have a disease. He put a bunch of measurements into the classifier, trained it, and look, it was 100% accurate! He was suspicious, so he put in a bunch of randomly generated numbers, trained it, and look, it was 100% accurate! Of course, neither version did any better than chance on data it hadn't been trained on.
In statistics it's called an unbiased estimator. Most people know it as an average. It doesn't have any particular link to crowds and the behaviour is very well defined. It does, however, require that the individual estimates be wrong in a random way.
You managed to pick exactly the same example I did.
Yes, that's what the article says. In a scientific paper that would be in the discussion, possibly in the conclusions. Experienced scientists know that the discussion, and depressingly frequently the conclusions, are BS the authors made up that's not really supported by the data, one way or the other.
I did read the article. Nothing in what you quoted is at all relevant. Perhaps you didn't understand my post?