1) Revenues collected by governments for public education in the United States totaled $593.7 billion. About $261.4 billion came from local sources, $258.2 billion from state sources, and $74 billion from federal sources.
2) That’s about $1,922 from each and every American.
3) Or $2,531 from each adult, 18 and older.
4) Or $4,567 from each non-farm American worker on a payroll.
5) That amounts to 11.4 percent of the average worker’s salary, or $2.20 per hour.
6) The average American employee thus works almost one hour every day to fund public schools.
7) It would take the entire salary of 14,842,500 employees to pay for U.S. public schools, equivalent to the entire retail trade workforce.
… in 1938, three systems of government were contending for global supremacy. One of them is still around: yours. Anglo-American liberal democracy. Had military luck favored either of the others – National Socialism or Marxist-Leninism – we can also be sure that it would have discovered and reveled in its foes’ every misdeed, and that it would have approached its own, if at all, tentatively and ambiguously.
If only one can survive, at least two must be illegitimate, and irredeemably criminal. And the survivor will certainly paint them as such. But suppose all three are irredemably criminal? If the third is an Orwellian mind-control state as well, its subjects are unlikely to regard it as such. It will certainly not prosecute itself.
The third, our third, is very different from the other two. We must remember that American democracy is categorically distinct from National Socialism and the people’s democracies in too many ways to count. Since there are too many ways to count, we will not bother counting them. We remain entitled to notice parallels. (For instance, it is almost more aesthetic criticism than political or economic analysis, but do read Wolfgang Schivelbusch’s Three New Deals.)
But no number of categorical distinctions from the other two can alter our estimate of the third’s criminality. There are as many ways to be a criminal as there are crimes. That we hang the murderer does not mean we must award a prize to the thief.
I must admit, this is a fascinating thought. I wonder, is it true? My recent readings of The Last Psychiatrist, and indeed my re-familiarization with Orwell’s 1984, make me think it is more true than I would like. Via Unqualified Reservations: A gentle introduction to Unqualified Reservations (part 1).
If you google “leading cause of injury to women”, you will immediately get a whole slew of links to domestic violence websites, where the “fact” that men are the leading cause of injury to women is repeated endlessly.
But it’s not true.
The leading cause of injury to women GLOBALLY is traffic. Yeah, cars are way more dangerous than men. The second leading cause of injury is a fall. Ladders are more dangerous than men.
Third place? “Intentional self-harm.” Via Louis C.K. says men are the number one threat to women. That’s not even close to being true, so why say it? | judgybitch.
Every time that a client visited the company or a new employee was hired, management would stop at my desk and point out that I was a woman. It sometimes felt like being a freak in a circus. It was unpleasant to be seen as something other than a skilled programmer. I once turned down a job offer because they really wanted to have a woman among their 40 male developers. I immediately thought of other candidates who will be turned down merely because they were male. The decision process seemed unfair. My sense of justice could not allow that, so I removed myself from the equation and gave all these men a fair chance.
And so every time that a conference asks for more women to submit, I am reminded of that job interview. Since having more women is a clear objective, then all decisions have to be weighed against it. Sure, we all want to think that we are not biased, but we are. As soon as we make something our mission, it inevitably affects our decisions. For me, conferences have nothing to do with gender. Gender is irrelevant. We’re here to talk about technology. When presented with two proposals on the same topic, I hope that a woman would not automatically win because someone wants to see a pie chart with equal slices. That is not what equal opportunity means. I am a woman, and I don’t want unfair advantages.
Do we really need to turn gender distribution into a problem? How exactly will the world be a better place with more women speakers? It’s just a number in a spreadsheet that some choose to find annoying. I’ll tell you what’s really annoying: people not automating tests, people withholding information about threats to projects, people not indexing their database tables or over-indexing them, people not using any cache, people skipping software analysis and design, etc. These are the beast that we need to slay. The rest is just a distraction, ready to suck all our time and deviate us from the path to knowledge and collaboration. When you review my application, please consider my skills, my character and the relevance of the topic for your audience. Don’t worry about my gender.
*That* is what a successful attitude looks like. Bravo, Anna. Via Anna Filina » IT Is About Technology, Not About Gender.
Then Robin Hanson of Overcoming Bias got up and just started Robin Hansonning at everybody. First he gave a long list of things that people could do to improve the effectiveness of their charitable donations. Then he declared that since almost no one does any of these, people don’t really care about charity, they’re just trying to look good. …
I have never seen a group of distinguished Berkeley faculty gain so sudden and intuitive an appreciation for the Athenians who decided to put Socrates to death. …
One of his claims that generated the most controversy was that instead of donating money to charity, you should invest the money at compound interest, then donate it to charity later after your investment has paid off – preferably just before you die, since donating money after death is legally complicated. His argument, nice and simple, was that the real rate of return on investment has been higher than the growth rate for 3000 years and this pattern shows no signs of changing. If you donate the money today, your donation grows with the growth rate, but if you invest it, it grows with the interest rate. He gave his classic example of Benjamin Franklin, who put his relatively meager earnings into a trust fund to be paid out two hundred years later; when they did, the money had grown to $7 million. He said that the reason people didn’t do this was that they wanted the social benefits of having given money away, which are unavailable if you wait until just before you die to do so.
And darn it, he was totally right. Not about the math – there are severe complications which I’ll bring up later – but about the psychology. On even the most cursory self-examination, my mind totally recoils at the thought of donating everything I’m going to donate to charity in a single lump sum just before I die. It just gibbers “But…but…you need to be a good person before then!” I’m not saying you can’t tear down Robin’s substantive argument in a bunch of good mathematical ways. I’m saying his ad hominem argument about my motivations seems to be true regardless.
Then he started talking about how you should only ever donate to one charity – the most effective. I’d heard this one before and even written essays speaking in favor of it, but it’s always been very hard for me and I’ve always chickened out. What Robin added was, once again, a psychological argument – that the reason this is so hard is that if charity is showing that you care, you want to show that you care about a lot of different things. Only donating to one charity robs you of opportunities to feel good when the many targets of your largesse come up and burdens you with scope insensitivity (my guess is that most people would feel more positive affect about someone who saved a thousand dogs and one cat than someone who saved two thousand dogs. The first person saved two things, the second person only saved one.) In retrospect this is absolutely true and my gibbering recoil at this problem isn’t just Yet Another Cognitive Bias but just good old self-interest.
If you are a product of your behavior, start wearing a watch again to discover who you actually are. If the sex addict gets a watch, hell, gets a calendar, what he will discover is that he has practiced no other skill more diligently than pursuing empty sex that he knows is unsatisfying to him. That’s what he’s spent the most time on, that’s what he knows how to do the best. Better than driving, better than speaking, better than Xbox– he has that mindset down to a reflex. So why would you expect he’d use any other technique for any other life problems that come up? If all you are is an expert hammerer, everything gets hammered.
You want to find empirical studies that show free trade to be harmful to free-trading nations? No problem; you can find them. You want to find empirical studies that show government stimulus spending to be a sure-cure for what ails a slumping economy? There are plenty of such data-rich studies out there. You want to find empirical studies that show that violent crimes aren’t deterred by the death penalty? Not a problem. You want to find empirical evidence that increased rates of handgun ownership increase citizens’ likelihood of dying of gunshot wounds? Many such studies are available.
You can also find plenty of empirical studies showing the opposite of what is shown by all of the above studies. And these other studies are, as a group, no less carefully done than are the studies that they contradict. And these other studies, also, are done by scholars no less credentialed and no less objective than are those scholars who produce the contrary findings.
That’s the reality of the social sciences. It’s not an exercise in simple observation of simple and self-defining facts, only one or two of which change at any time.
via Where Are My Data?!.
When there are many factors that have an impact on a system, statistical analysis yields unreliable results. Computer simulations give you exquisitely precise unreliable results. Those who run such simulations and call what they do “science” are deceiving themselves.
Beware also of models that fit historical data (especially “corrected” or “adjusted” data) but do not provide accurate predictions. This applies to macroeconomics, climate change, the stock market, social “sciences”, and other complex systems with high causal density. You have to be very very careful you aren’t fooling yourself with these models; and, as noted by Feynman, “yourself” is the easiest person to fool. Via Causal Density is a Bear | askblog.