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Category: Philosophy

The philosophy of science, empiricism, a priori reasoning, epistemology, and so on.

December 24, 2009 | 11 Comments

Christmas Eve Party Game: Spot the Logical Fallacy!

What better way to celebrate Christmas Eve than with a game the whole family can play? So gather round the tree, load up the eggnog with some Barbancourt 5 star, and stand by for fun!

Rules: Each question begins with an illustrative scenario, after which follows one or more puzzlers. Points are awarded based on difficulty.

  1. Shauna Wilton, a female professor of political sciences at the University of Alberta has it in for Thomas the Tank Engine, which is England’s version of Barney, but on wheels. Wilton has academically analyzed 23—count ’em!—Thomas episodes and doesn’t like the way they portray women! She wants it changed! Now! Here’s what she says:

    The female characters weren’t necessarily portrayed any more negatively than the male characters or the male trains, but they did tend to play more secondary roles and they’re often portrayed as being bossy or know-it-alls.

    Bossy. Hmmm. More from the story:

    [Wilton] also objected to the way the show portrays Thomas, Percy and James slaving away for wealthy bosses like the Fat Controller.

    Turns out that that darn Thomas is a…a…a conservative! And the children that watch him “will [someday] attain full political citizenship, and the opinions and world outlook they develop now, partially influenced by shows like Thomas, are part of that process.”

    10 points Now for the question, in the form of a statement: The University of Alberta charges its students tuition. Criticize.

    Hat tip to reader and contributer Ari Schwartz.

  2. Paul Kotta, a Livermore, California resident, in a letter to the New York Times (D) called people who do not subscribe, as he religiously does, to the Anthropogenic Greenhouse Warming theory of climate, “deniers.” He argues that “[o]ver the years, various industries have launched coordinated propaganda efforts to deny now accepted facts like the cancer-causing effects of tobacco or that seat belts save lives.” He adds that some industries now deny “the role of pollution in climate change.” Therefore, AGW is true.

    20 points Question: has Kotta soaked up too much California sun, or has he hit upon a brand new logical proof of AGW?

  3. Houston Baker, now a “distinguished” professor of English at Vanderbilt, was a professor at Duke, and was one of the 88 professors who published an open letter condemning the Lacrosse team players falsely accused of rape.

    In June 2006, Baker falsely suggested that Duke lacrosse players had raped other women. In a pervasively ugly response to a polite e-mail from the mother of a Duke lacrosse player, he called the team “a scummy bunch of white males” and the woman the “mother of a ‘farm animal.’ “

    What fun! And what a beautiful use of the English language from a “distinguished” professor of the same. (Nobody has ever discovered whether he apologized—-but your intrepid reporter has emailed him: hold your breath until we receive a response.)

    Vanderbilt loved Baker’s prose, even if you didn’t, and they hired him away from Duke. (Diversity! Diversity!) There, he wrote the book Betrayal: How Black Intellectuals Have Abandoned the Ideals of the Civil Rights Era, which accuses many black intellectuals of, among other crimes, “centrism”, which are activities conducted at the expense of the “black majority.”

    One of his arguments is that the prison population is rising (it has since fallen), and that some prisoners are black (they are). Baker suspects the “prison-industrial complex”, whereby some private companies build and run prisons, of making profits (they do). His implication is that the new prisons that are built must be filled else the companies involved won’t profit (true). Therefore, the “complex”, through nefarious means, generates incarcerations.

    10 points Question 1 (non-logical): Define distinguished.

    30 points Question 2: What came first, the criminal or his cage?

  4. Congressman Alan Grayson (D – Florida), who hobbies include chasing ambulances and soliciting for his own personal “money bomb“, was irked, irritated, and downright incensed that citizen Angie Langley created the voodoo website MyCongressmanIsNuts.com. So peeved was Grayson that he wrote our illustrious Attorney General (the same gentleman who wants to bring the 9/11 murderers to New York City because, uh, well, just because) and demanded that the United States government “imprison [Angie Langley] for 5 years” for speaking poorly of him.

    Part of the United States’s Constitution—the supreme law of the land, trumping, for now, even “progressive” politicians—says, and I quote:

    Congress shall make no law..abridging the freedom of speech, or of the press

    To repeat: Congressman Alan Grayson (D – Florida) is a congressman, a guardian of our Constitution.

    10 points Question 1 (non-logical): How much money could an energetic trial lawyer hope to pull down in a year if he charges a contingency fee of thirty-three percent?

    40 points Question 2: How many people can you arrest for political dissent before you violate the Constitution.?

That’s it for now. Have a ball and be sure to check back for our New Year’s game: What Kind of a Dumb Idea Was That?

December 10, 2009 | 15 Comments

Homogenization of temperature series: Part II

Be sure to see: Part I, Part II, Part III, Part IV, Part V

Aside: counterfactuals

A counterfactual is statement saying what would be the case if its conditional were true. Like, “Germany would have won WWII if Hitler did not invade Russia.” Or, “The temperature at our spot would be X if no city existed.” Counterfactuals do not make statements about what really is, but only what might have been given something that wasn’t true was true.

They are sometimes practical. Credit card firms face counterfactuals each time they deny a loan and say, “This person will default if we issue him a card.” Since the decision to issue a card is based on some model or other decision process, the company can never directly verify whether its model is skillful, because they will never issue the card to find out whether or not its holder defaults. In short, counterfactuals can be interesting, but they cannot change what physically happened.

However, probability can handle counterfactuals, so it is not a mistake to seek their quantification. That is, we can assign easily a probability to the Hitler, credit card, or temperature question (given additional information about models, etc.).

Asking what the temperature would be at our spot had there not been a city is certainly a counterfactual. Another is to ask what the temperature of the field would have been given there was a city. This also is a strange question to ask.

Why would we want to know what the temperature of a non-existent city would have been? Usually, to ask how much more humans who don’t live in the city at this moment might have influenced the temperature in the city now. Confusing? The idea is if we had a long series in one spot, surrounded by a city that was constant in size and make up, we could tell if there were a trend in that series, a trend that was caused by factors not directly associated with our city (but was related to, say, the rest of the Earth’s population).

But since the city around our spot has changed, if we want to estimate this external influence, we have to guess what the temperature would have been if either the city was always there or always wasn’t. Either way, we are guessing a counterfactual.

The thing to take away is that the guess is complicated and surrounded by many uncertainties. It is certainly not as clear cut as we normally hear. Importantly, just as with the credit card example, we can never verify whether our temperature guess is accurate or not.

Intermission: uncertainty bounds and global average temperature

This guess would—should!—have a plus and minus attached to it, some guidance of how certain we are of the guess. Technically, we want the predictive uncertainty of the guess, and not the parametric uncertainty. The predictive uncertainty tells us the plus and minus bounds in the units of actual temperature. Parametric uncertainty states those bounds in terms of the parameters of the statistical model. Near as I can tell (which means I might be wrong), GHCN and, inter alia, Mann use parametric uncertainty to state their results: the gist being that they are, in the end, too confident of themselves.

(See this post for a distinction between the two; the predictive uncertainty is always larger than the parametric, usually by two to ten times as much. Also see this marvelous collection of class notes.)

OK. We have our guess of what the temperature might have been had the city not been there (or if the city was always there), and we have said that that guess should come attached with plus/minus bounds of its uncertainty. These bounds should be super-glued to the guess, and coated with kryptonite so that even Superman couldn’t detach them.

Alas, they are usually tied loosely with cheap string from a dollar store. The bounds fall off at the lightest touch. This is bad news.

It is bad because our guess of the temperature is then given to others who use it to compute, among other things, the global average temperature (GAT). The GAT is itself a conglomeration of measurements from sites all over (a very small—and changing—portion) of the globe. Sometimes the GAT is a straight average, sometimes not, but the resulting GAT is itself uncertain.

Even if we ignored the plus/minus bounds from our guessed temperatures, and also ignored it from all the other spots that go into the GAT, the act of calculating the GAT ensures that it must carry its own plus/minus bounds—which should always be stated (and such that they are with respect to the predictive, and not parametric uncertainty).

But if the bounds from our guessed temperature aren’t attached, then the eventual bounds of the GAT will be far, far, too narrow. The gist: we will be way too certain of ourselves.

We haven’t even started on why the GAT is such a poor estimate for the global average temperature. We’ll come to these objections another day, but for now remember two admonitions. No thing experiences GAT, physical objects can only experience the temperature of where they are. Since the GAT contains a large (but not large enough) number of stations, any individual station—as Dick Lindzen is always reminding us—is, at best, only weakly correlated with the GAT.

But enough of this, save we should remember that these admonitions hold whatever homogenization scenario we are in.

Next time

More scenarios!

My travails of a week ago, battling the air at thirty-eight thousand feet was such a life-affirming experience that I have decided to repeat it. From this afternoon, I will be out of contact for a day or so.

Be sure to see: Part I, Part II, Part III, Part IV, Part V

November 22, 2009 | 22 Comments

Climategate Peer Review: Science red in tooth and claw

See also see this story on proxies

I am a scientist and I have lived around fellow scientists for many years and I know their feeding habits well. I therefore know that the members of our secular priesthood are ordinary folk. But civilians were blind to this fact because our public relations department has labored hard to tell the world of our sanctity. “Scientists use peer review which is scientific and allows ex cathedra utterances. Amen.”

But the CRU “climategate” emails have revealed the truth that scientists are just people and that peer review is saturated with favoritism, and this has shocked many civilians. It has shaken their faith and left them sputtering. They awoke to the horrible truth: Scientists are just people!

Now all the world can see that scientists, like their civilians brothers, are nasty, brutish, and short-tempered. They are prejudiced, spiteful, and just downright unfriendly. They are catty, vindictive, scornful, manipulative, narrow-minded, and nearly incapable of admitting to a mistake. And they are cliquey.

Thus, we see that the CRU crew define a “good scientist” as one who agrees with them, a “bad scientist” or “no scientist” as one who does not agree with them, and a “mediocre scientist” as somebody who mostly agrees with them. Further, these judgments are carried to the peer-review process.

Claiming lack of peer review was once a reasonable weapon in scientists’ argument armamentarium. After climategate, all can see that this line of logic is as effective as a paper sword.

Alfred's Global Warming Poem

For example: the CRU crew publicly cry, “If our skeptics had anything to say, let them do it through peer review, otherwise their claims don’t count.” Never mind that this parry is a logical fallacy—an argument is not refuted because it was uttered outside a members-only journal. Pay attention to what they say privately:

Proving bad behavior [about peer review] is very difficult. If you think that [Geophysical Research Letters editor] Saiers is in the greenhouse skeptics camp, then, if we can find documentary evidence of this, we could go through official AGU channels to get him ousted.1

They say that this journal or that one, because it dared publish peer-reviewed work that did not agree with the CRU consensus should be banished from the fold, and that its editors should resign or be booted, and that everybody should agree not to cite papers from those journals, and so on.

In other words, use muscle and not mind if you don’t like the results. Get rid of the editor and put an agreeable apparatchik in his place.

Another popular thrust: claim that it wasn’t real, genuine, honest-to-goodness peer review that led to skeptical findings being published. Something must have gone horribly wrong for those papers to have seen the light of day! Peer reviewed is thus implicitly defined as that process which publishes only those views that agree with prior convictions.

Sensing that that tactic could fail, some said, “Aha!, let’s see if we can disparage the authors of those skeptical papers: if we can successfully savage and malign them, then their findings are wrong.”

Yes, sir, dear reader, you guessed it. Another logical fallacy. It is absolutely no argument whatsoever to say a finding is wrong because its purveyor is “not a real climatologist” or “has not published much” or that he “has few citations from previous papers.”

It is also a fallacy to say that because a skeptical argument has appeared on a website—and could not pass through the gauntlet of the good-old-boy peer review system—that it need not be answered.

Here’s some advice to my fellow scientists: If an argument appears on a website, or on FOX news, or in a newspaper, or even on the back of the t-shirt, and that argument fails, then simply say so and say why. And then be done with it. Do not make an ass of yourself by claiming that answering criticisms that do not come from your circle of friends is beneath you.

If an argument that is old and has been well refuted elsewhere, say so, and say where a reliable refutation may be found. It makes you look desperate and foolish to say that the argument came from a blogger and is therefore suspect. And it makes people believe the blogger.

Anyway, do not cry foul over skeptical blogs and then simultaneously publish your own blog to disseminate your own beliefs. “They can’t publish a blog but we can.” That just looks stupid.

But don’t let’s get too carried away, everybody. These kind of behind-the-scenes activities, perhaps more heated in some respects, are the same in every field. Climate scientists are people and so are scientists in other areas. Bad behavior is nothing new and will never change, because people will always be people.

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1I wrote to the author of those words and asked, “I can understand that you feel strongly about the matter, but does your conviction run to harming the career of a fellow scientist merely because he disagrees with you?” I’ll let you know if I receive and answer.

See also see this story on proxies

August 1, 2009 | 21 Comments

Models, theories, consistency, and truth

Ready? Put on your best straight face, recall that global temperatures have not increased for a decade, and that it’s actually been getting cooler, then repeat with Brenda Ekwurzel, of the Union of Concerned Scientists—what they’re concerned about, heaven knows; perhaps replace “concerned” with “perpetually nervous”—repeat, I say, the following words: “global warming made it less cool.”

Did you snicker? Smile? Titter? Roll your eyes, scoff, execrate, deprecate, or otherwise excoriate? Then to the back of the class with you! Because what Ekwurzel said was not wrong, because it is true that the theory of global warming is consistent with cooler temperatures. The magic happens in the word consistent.

To explain.

While there might be plenty of practical shades of use and definition, there is no logical difference between a theory and a model. The only distinctions that can be drawn certainly are between mathematical and empirical theorems. In math, axioms—which are propositions assumed without evidence to be true—enable strings of deductions to follow. Mathematical theories are these deductions, they are tautologies and, thus, are true.

Empirical theories, while they might use math, are not math, and instead say something about contingent events, which are events that depend on the universe being in a certain way, outcomes which are not necessary, like temperature in global warming theory. Other examples: quantum mechanics, genetics, proteomics, sociology, and all statistical models: all models that are of practical interest to humans.

Just like with math, empirical models start with a list of beliefs or premises, again, some of which might be mathematical, but most are not. Many premises are matters of observation, even humble ones like “The temperature in 1880 was cooler than in 1998.” The premises in empirical models might be true or uncertain but taken to be certain; except in pedantic examples, they are never known to be false.

It is obvious that the predictions of statistical models are probabilistic: these say events happen with a probability different than 0 or 1, between certainly false and certainly true. Suppose the event X happens, where X is a stand-in for some proposition like “The temperature in 2009 will be less than in 2008.” Also suppose a statistical theory of which we have an interest has previously made the prediction, “The probability of X is very, very small.” An event which was extraordinarily improbable with respect to our theory has occurred. Do we have a conflict?

Global warming cools things off

No, we do not. The existence of X is consistent—logically compatible—with our theory because our theory did not say that X was impossible, merely improbable. So, again, any theory that makes probabilistic predictions will be consistent with any eventual observations.

Global warming is a statistical theory. Of course, nowhere is written down a strict definition of global warming; two people will envision two different theories, typically at the edges of the models. And this is not unusual: many empirical theories are amorphous and malleable in exactly the same way. This looseness is partly what makes global warming a statistical theory. For example, for nobody I know, does the statement “Global warming says it is impossible that the temperature in any year will fall” hold true. The theory may, depending on its version, say that the probability of falling temperatures is low, and as low as you like without being exactly 0; but then any temperature that is eventually observed—even dramatically cold ones—are not inconsistent with the theory. That is, the theory cannot been falsified1 by observing falling temperatures.

It is worth mentioning that global warming, and many other theories, incorporate statistical models that give positive probability to events that are known to be impossible given other evidence. For example, given the standard model in physics, temperature can fall no lower than absolute zero. The statistical global warming model gives positive probability to events lower than absolute zero (because it uses normal distributions as bases; more on this at a later date). But even so, the probabilistic predictions made by the model are obviously never inconsistent with whatever temperatures are observed.

Incidentally, even strong theories, like, say, those used to track collisions at the Large Hadron Collider, which are far less malleable than many empirical models, are probabilistic because a certain amount of measurement error is expected; this ensures its statistical nature (space is too short to prove this).

Now, since, for nearly all models, any observations realized are never inconsistent with the models’ predictions, how can we separate good models from bad ones? Only one way: the models’ usefulness in making decisions. “Usefulness” can mean, and probably will mean, different things to different people—it might be measured in terms of money, or of emotion, or by combination of the two, or by how the model fits in with another model, or by anything. If somebody makes a decision based on the prediction of a model, then they have some “usefulness” or “utility” in mind. To determine goodness, all we can do is to see how our decisions would have been effected if the model had made better predictions (better in the sense that its predictions gave higher probability to the events that actually occurred).

Unfortunately for Ekwurzel, while she’s not wrong in her odd claim, global warming theory has not been especially useful for most decision makers (those that make their utility on the basis of temperature and not on the model’s political implications). It is trivial to say that the theory might be eventually useful, and then again it might not. So far, the safe bet has been on not.

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1Please, God, no more discussions of Popper and his “irrational” (to quote Searle) philosophy. This means you, PG!