By popular demand ("this one guy asked for it once"), I've added a post index to iRi. (Also, Google has lost a lot of my pages, which sucks mostly because I keep trying to use it on my own site.)
I tried to implement something like Amazon's Statistically Improbable Phrases, which take characteristic phrases out of books and works pretty well, but my corpus is too small. There are many words I use only once, and the vast majority of two-word phrases are entirely unique. Consequently, I use only single words, and even that works poorly.
While I failed in my goal, I decided the result was pleasantly surrealistic, so I kept it in anyhow. Word-based algorithms are so much fun sometimes, even when they completely fail. It's quirky and I know it. It really loves to highlight misspellings, for instance.
(Also, the process runs once a day, so for instance this post won't be there right away. That's OK.)
I had the original calendar-based archiving system initially, but I just don't think that works very well for weblogs. Who wants to go to "March 20, 2002"? It certainly doesn't work well with less than a post per day.
All in all, I feel like I fared well for a site like Reddit, but there was one repeated theme in the comments I wanted to address: The idea that economics would be impossible to teach in high school. The argument was that economics is hard in the sense that true understanding requires advanced math, that economics is controversial in the sense that there is no one accepted theory of economics, and that having a partial understanding of economics could even be worse than no understanding at all in some cases.
All of these things are true. However... for what thing that we teach in high school are these objections not applicable to? The only exception is that arguably you don't need math for some subjects, but every other clause holds across every subject that doesn't solely consist of learning the names of things.
Even if children were perfectly logical machines that could be successfully taught by starting at "the beginning" and brought up in a strictly-proceeding progression of knowledge starting on that foundation, an educational theory that could charitably be described as "disconnected from reality", there's just too much "foundation" to learn. The most foundational discipline I can think of is number theory, and we're not going to be teaching that to five-year-olds any time soon. We have to start by teaching consensus-based approximations of complicated theories, or we'll never have anything to actually teach.
I am quite confident that a high-school curriculum for game theory and economics could be produced that would both satisfy my desires and fit right into to all the other over-simplified explanations of vastly complicated topics that the student lacks the tools or experience to truly appreciate that we are pleased to call the "curriculum" today.
Following up on my "failed predictions" point, I point at the now widely-distributed article about the low-fat vs. low-carb diets.
The standard dietary orthodoxy predicts that the results of this study would be exactly the opposite of what happened. The predictions are wrong. Therefore, the standard model is wrong. I don't need to be a nutritionist to make this determination.
I don't know what the right model is. I think that's pretty sad, considering that if nutritionists hadn't gotten bogged down by a premature orthodoxy, we would probably be now in the position of refining a solid idea, instead of where we really are now, which is quite nearly square one.
Again, the value of post-facto corrections made to predict previous results is zero or less; if a nutritional theory can't predict it's just plain no good. Previous studies pointed in this direction years ago, but they were shorter-term studies, so the dietary orthodoxy was updated to say oh, sure, maybe higher fat diets work at first but in the long term they will fail. This study is important because it's the first big long-term study. Science would have been better off to take those first studies, which still completely violated the predictions of the models, more seriously.
(I recognize that when your models are off a little bit, it is better to try to fix them up than to just junk them. When your models are 100%, 180-degrees-opposed wrong on a grand scale, you're usually better off junking them. No matter how emotionally attached to them you are.)
Over the past couple of years, I've been turning into a skeptic on the global warming theory, in particular the idea that mankind's actions have effectively doomed us to an uncomfortably hot planet (since the putatively required solutions are all completely unimplementable).
I will grant that my politics would seem to incline me to such skepticism, but I try to decide based on the science, not the politics. If the world truly is heading for disaster, I want to know.
It is very hard to judge a science that you have no experience in, but there is one metric that you can correctly use as an educated outsider to determine whether a scientist is on the right track or the wrong track: the accuracy of predictions. If a prediction is correctly made, it favors a theory, proportionally to the difficulty of the prediction. If the prediction is wrong, it is very solid evidence that the theory or model is wrong. This judgment can be often be made by anybody, especially when it's a question of something simple like temperature.
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