Conventional Wisdom or Propaganda?

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It is conventional to sing the praises of private schools while dismissing public schools as yet another example of Government’s ineffective nature. That rhetoric is part of the Republican campaign to undermine voter confidence in state based solutions. It’s a natural outgrowth of the Republican party’s real goal: to lower taxes and increase wealth disparity. You can’t achieve that goal if most of the public likes the services the government provides; i.e. health, transportation, safety, education.

So it’s with some amusement that I read this item from the New York Times.


WASHINGTON, July 14 – The Education Department reported on Friday that children in public schools generally performed as well or better in reading and mathematics than comparable children in private schools. The exception was in eighth-grade reading, where the private school counterparts fared better.

The report, which compared fourth- and eighth-grade reading and math scores in 2003 from nearly 7,000 public schools and ore than 530 private schools, found that fourth graders attending public school did significantly better in math than comparable fourth graders in private schools. Additionally, it found that students in conservative Christian schools lagged significantly behind their counterparts in public schools on eighth-grade math.

Conventional wisdom is wrong it is just Republican Propaganda. Public schools may not be as good as we’d like, but private schools aren’t any better.

Blog Payolla!

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A fun article in a recent the New Yorker about a radio station in New York City mentions in passing that Eliot Spitzer the NY attorney general is currently investigating a bunch of radio stations for taking payola. I’m kind of glad, if surpised, that there are still consumer protection laws on the books about that.

Meanwhile bloggers can now take payola, see over here.

This article about blogger payola is wonderfully ironic once you notice the amazing assortment of advertising techniques in use by it’s web site.

Polarized America

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I’ve been awaiting this book for months; and I finally got a copy. Polarized America: The Dance of Ideology and Unequal Riches by Nolan McCarty, Keith T. Poole, and Howard Rosenthal. I paid full price, which is both totally out of character and an indication of how very important I think this book is, but you don’t have to.

This book’s big picture is that very key statistics have all move near lock step very rapidly over the last 25 years in: income distribution, political polarization, percentage foriegn born, declining local government services, and others. These are connected in a complex dance.

Here’s something I didn’t realize. While the Republican party has been moving rapidly right; the Democratic party has on the one hand abandoned their advocacy of general welfare platforms and shifted toward a what they notably refer to as issues of ascription. These are direct decendents of the civil rights movement. These are issues about ascriptive characteristics (race, gender, sexual preference) of individuals. We should reclaim the general welfare issues!

Availablity

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Here’s some more fun stuff gleaned from the book I’m reading.

One of the canonical reasons for poor judgement is known as availablity; i.e. we think and work using the tools that are easily at hand. If a tool is beyond reach we are far less likely to apply that tool. There are lot of examples. The folks that plan for floods, for example, rarely plan for floods other than those they have experienced. If your asked a mess of people to estimate how many words start with the letter r, like road, v.s. how many end with the letter r, like tour they will get the wrong answer, begins with, because your noodle is set up to recall words by their first rather than their last letter. I love the variant of that example; people will guess that abstract nouns, like love, hate, truth, are occur more commonly than concrete knowns, like door, street, bicycle. Apparently people have an easier time recalling abstract nouns v.s. concrete ones. Who knows why, possibly because the abstract nouns cover broad swaths of experiance.

In reading about availablity, and the other insights outlined in this book, I find myself thinking about how they get mixed into the ways people market products, debate issues, manage planning, and even how you could create carnival games out of them. One reason a component manufature has to give way a huge number of free samples is to assure that his components are highly available at the moment when some random designer is reaching out to pick something up to solve his problem. That’s one reason Open Source works; it adopts a r-Strategy.

This example of availably is particularly thought provoking. A reasonably standard formal way to estimate risk is to create a fault tree. You can view lots of examples at Google Images. The process of making a fault tree is lot like the process people use in making any plan. You attempt to collect all the contengencies and then sort out their likelyhood and dependencies. For example in thinking about why the car might not start you might include dead battery and left headlights on by mistake. Professional planning and fault tree work involves getting experts to help. You might do that by doing surveys and investigations of various car starting falures; or you might interview experts (say are mechanics) and have them help generate contengencies and probablities of those contengencies.

Because of availablity asking the experts does not work.

Say you have methodically assembled a large and nominally complete fault tree and because you doubt you’ve thought of everything you include a node for “other causes.” At that point your fault tree covers a 100 percent of the failure scenerios. You go to the experts and ask them to help by assigning 100 points (i.e. percentage chance) across the perimeter of the tree.

Why doesn’t that work?

It doesn’t work because studies show that you get radically different answers from the experts if you check their work by varying the fault tree you present. If you have a tree with 10 nodes and you collapse 2 or 3 into the “other causes” node the experts will then raise their estimates for all the remaining causes. Because the nodes you merged into “other causes” are no longer easilly available.

Of course what’s in that “other causes” node is the long tail of contengencies.

Learning at the Knee of a Random Number Generator

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Here’s a thought provoking intersection between behaviorism and statistical thinking; plucked out of this book.

Here’s a very naive model of behaviorism: If the animal behaves well we reward him, and if he behaves poorly we punish him. This primitive version of behaviorism is fraught with problems; but it will do for this discussion.

A very naive statistical model of behavior breaks into two parts; with average behavior and random behavior around that. Animal trainers are experts in leveraging that random bit. If you want to train a goldfish to swim clockwise then before you feed him then you wait for the random clockwise turn before feeding.

Of course animal training is a two way street. Pets expend a great deal of effort attempting to train their owners to feed them. It’s fun to walk in front of the tanks at a large pet store wearing the same color shirt as the staff an watch the fish attempt to trigger your into feeding them.

The hope of training is that you shift the average; but that takes time and in the meanwhile random variations will generate occasional good and bad performances relative to the mean.

So here’s the rub. If the animal behaves in an exceptionally good or bad manner it is likely that in following period his behaviors will return to the previous average behavior. In the jargon of statistics this is an example of regression to the mean.

Regression to the mean is enough to train a bad behavior in the trainer! Consider this scenario: the animal behaves well, the trainer rewards him, and then in the following training rounds the animal is certain to regress back toward his average behavior. The trainer learns from that the reward triggered the regression. The trainer learns not to reward. Which is bogus.

But it get’s worse. Consider this scenario: the animal behaves badly, the trainer punishes the behavior, and then in the following rounds the animal’s behavior randomly regresses back to the mean. The trainer learns that punishment precedes behavior improvements and; not because the animal is learning anything but because the statistics say so. The statistics alone are enough to train the trainer to punish bad behavior but not reward good behavior.

This is very bad!  It’s a fundamental insight of sophisticated behaviorism that punishment is far less effective than rewards; so much so that punishment often doesn’t work at all! Only a stupid or a captive animal will put up with training based on punishment. This problem is redoubled because if you punish the animals become more cautious; which reduces the not just the random variance (which you need) but also suppresses the smart active searching you want the animals doing. Punishment doesn’t work on smart animals and when you can get away with it makes the animal become stupid.

What a mess! Notice that you don’t need an animal to teach the trainer this bogus behavior pattern of never reward, but do punish. If you had the trainer work to train a random number generator he’d learn the same lesson. There really isn’t a more stupid beast than a random number generator. Which I think goes a long way toward explaining why fans of punishment often describe the animals they are trying to train as stupid.

Hans Rosling

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Cool! Hans Rosling has a blog. Hans is one of the principles behind Gapminder which I posted about a long time ago.

Reading Charles Tilly’s book on how we explain stuff has lead to buzzing in my head about conventional wisdom. We all have lots of these conventional bits of wisdom we use to explain things. For example: Question:”Why do they do that?” Awnser: “For the money.” We collect these into little internal FAQs. That Q&A is taken from the booklet labeled ‘rational economic-man.’ Each of the booklet we collect is self consistent.

Together these Catechisms let us move quickly through our days. It’s a very effective heuristic. It’s always comforting to be able to explain the world. It makes it seem safer.

Trouble arises when these rules of thumb are wrong in material ways. That “in it for the money” rule is unlikely to be useful in social spheres, for example. Distance helps to reduce the chance that a mistake will have consequences. If you’re a Fortune 500 company you may not occupy any social sphere and the rule above will do just fine. Living in the US a poor explaination for why HIV infection rates are 27% in South Africa is less likely to materially effect your life.

These days people like to go on about how the world is getting smaller and how the boundaries between spheres, particularly geographic ones, are getting thinner and thinner. In so far as that is true the risk of living with a consistent but flawed Catachism is increasing. There is a rising tension between a Reality Based v.s. Faith Based scheme for moving through your days. Which is a huge pain in the neck! Nobody, and I mean nobody, has the time to get through a day deriving each action from first principles.

Hans Rosling knows stuff, based on facts, that won’t fit your default rule book. For example how do explain the 2% HIV infection rate in Sudan v.s. the 27% rate in South Africa? Did you know that electricity is good for infant survival rates independent of income?


An evidence base world view requires five thoughts at the same time:
1. World is getting better and better,
2. but at the cost of climate change,
3. and billions still live miserable lives in poverty
4. and in the last decade life got worse for 100 of millions,
5. but as the world is stupidly managed, we have many opportunities to fix the world for the grandkids!

Go forth, read and subscribe.

grep -o

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If only one could know which skills will be worth learning! The time I invested in learning about APL, Ada, Cobol, RSX/11, Focal, Snobol, 6809 assembler, etc. etc. didn’t return much value beyond amusement, entertainment, and experiance.

Learning all the Unix tools back in 1977 was fun too it has been extremely valuable too!

Sometimes I discover that since then somebody has added a new tool; or a new switch to existing one. Today I learned about the -o switch to grep. It prints out only the matching string; not the whole line.


536$ grep -o '[a-z][a-z]*:[a-z][a-z]*' cascades.rdf | sort | uniq
foaf:name
my:author
my:editor
ow:address
ow:author
ow:booktitle
ow:editor
ow:institution
ow:journal
ow:month
...

Useful.

Network Neutrality

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I’ve not been following the net neutrality debate, so I presume all these points have been made by others. But I want to firm up my thoughts, just for fun.

There are a few frames you might map this into.

The traditional telco regulatory framing is about monopoly power v.s. the little guy. This framing the monopoly power of the telco arises from network effects and physical realities. The state steps in to help coordinate the creation of the monopoly; handing out one of a like license for airwaves and utility poles. The state also steps into limit the perfectly natural tendency for capital to abuse thier monopolies at any oportunity. This framing is all perfectly valid; etc. etc. In the current US poltical ecology it also write it’s own outcome. Capital wins, the little guy looses; an any public good is converted to a private good in the hands of the highest bidder. The only question is who runs the auction; the state or the legislators.

A second frame to drop this debate was nicely coined by Martin; ‘What’s the label on the tin?” Markets work smoothly, scale up quickly, and generate lots of wealth and externalities when the transactions can be executed quickly. That requires setting standards; those standards reduce what aspects of each transaction you need to negotiate. The state gets involved in these debates because of it’s unique power to set standards. Markets participants have a love/hate relationship with this standards making process. They love it because in the best scenarios everybody wins; and they hate it because during the game individual actors can sometimes capture huge benefits for their class of actors. You can predict which standards battle will be long v.s. short using various means. In this case I’d predict a long drawn out battle.

Yet another frame we can drop this into is old v.s. new capital. The distinquishing characteristic of old capital is that it tends to be much more politically connected and conservative. New capital has weak political muscles; since while it’s got them it hasn’t practiced using them. In this story we cast the telcos in the role of old capital and the new web businesses in the role of new capital. The new guys are a complementary industry of the old guys. The old guys would like a peice of the action. So they are looking to get the power to charge the new guys to deliver content over them. This frame predicts that the key question is can old capital move fast to lock-in advantagous regulations; faster than new capital can figure out how to use those untrained political muscles. I think that’s obvious new capital will learn quickly enough. That’s clear because they have common cause with some other large players: media, device makers, and software plaform vendors. Those three already played a round in this frame during the HDTV standards battles. If we presume that then we can also predict that this standards battle will be quite drawn out. Two very wealthy industries competing for the state’s attention is not a recipe for a quick resolution. Bearing that in mind I read this report as indicating that Alen Specter has recognized that could generate a lot of campaign contributions for a very long time.

It was unclear precisely what approach the Judiciary Committee would take. Specter, for one, indicated that he would prefer looking at the issue on a “case-by-case” basis rather than issuing a “general rule” about what network operators can and cannot do–an approach favored by Internet companies. He said it may be more productive to negotiate less formal “standards” for network access with the players involved because writing new laws is “extraordinarily difficult, candidly, when you have the giants on both sides of these issues.”

The final frame I notice in this discussion is how the telco industry is undergoing a very very fundimental shift. The telco industry does distirbution or brokage; like roads, canals, airlines, UPS, eBay, match makers, etc. Traditionally they transported phone calls; one end you place the call, the other end would recieve the call. Note how there are two kinds of actor there; that’s true in all these industries. If you and I play in both roles from day to day – we make calls, and we recieve calls. There are different labels for the two roles. In the internet we call them client and server. At eBay and other markets you call them buyer and seller. The match maker calls them wife and husband; or employee and employeer. The media industry calls the content producers and consumers. Most of the new capital businesses, ebay, google, etc. have very sharp distinctions between the two roles. They often charge one side and the other; and they always have very different pricing schemes for the two sides.

Telco is a interesting case, because historcially it had a reasonably weak two sided network nature. That’s changing, and fast. The emergance of the large web properties who serve vast populations of users means the telcos are now two sided businesses; but only if they can get the regulations written when they weren’t revised to allow them new forms of pricing power.

This frame has some hints in it about how what I suspect will be a very long drawn out standards/regulatory battle might be resolved. This is about how to label the tin; and both old and new capital find that a very puzzling problem. I’m bemused by the thought that the giant web properties might remain “free” by having the telco’s pay them; which is more or less the model uses in the cable TV industry. It’s an ugly outcome; but it’s consistent with the current political ecology; where the little guy doesn’t even have a seat at the table.

“Hope and fear are inseparable”

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Can the dollar be talked down gradually? Consensus economic models say no: once market expectations are that the dollar will be sharply lower in five years, speculators will make the dollar sharply lower tomorrow.

Nevertheless, there is hope: consensus economic models say the dollar crashed three years ago.

— Brad DeLong