This is the essay I’ve been meaning to write, but not taken the time. Fortunately, someone else did:
Consensus, in and of itself, is not necessarily a bad thing. The more easily testable and verifiable a theory, the less debate we would expect. There is little disagreement, for example, about the sum of one plus one or the average distance of the earth from the sun. But as a question becomes more complex and less testable, we would expect an increasing level of disagreement and a lessening of the consensus—think: the existence of god, the best band since the Beatles, or the grand unified theory of physics. On such topics, independent minds can—and should—differ.
We can use a simple formula to express how an idea’s popularity correlates with its verifiability. Let us introduce the K/C ratio—the ratio of “knowability,” a broad term loosely encapsulating how possible it is to reduce uncertainty about an idea’s correctness, to “consensus,” a measure of the idea’s popularity and general acceptance. Topics that are easily knowable (K ~ 1) should have a high degree of consensus (C ~ 1), whereas those that are impossible to verify (K ~ 0) should have a low degree of consensus (C ~ 0). When the ratio deviates too far from the perfect ratio of 1, either from too much consensus or too little, there is a mispricing of knowledge. Indeed, in cases of extreme deviations from the perfect ratio, additional support for a concept with such a lopsided K/C ratio increasingly subtracts from its potential veracity. This occurs because ideas exist not simply at a single temporal point, but rather evolve over the sweep of time. At the upper reaches of consensus, there is less updating of views to account for new information—so much so that supporters of the status quo tend to suppress new facts and hypothesis. Government agencies deny funding to ‘sham’ scientists, tenure boards dissuade young researchers from pursuing ‘the wrong’ track, and the establishment quashes heretical ideas.
…To see how this works in practice, we turn to the evergreen topic of climate change. Notwithstanding the underlying ecological threat of climate change itself, the debate about how to confront human-caused global warming has spawned unprecedented financial, political, and social risks of its own. Entire industries face extinction as the world’s governments seek to impose trillions of dollars of taxes on carbon emissions. The New York Times’s Thomas Friedman approvingly writes that Australian politicians—not to mention public figures through the world—now risk “political suicide” if they deny climate change. But if carbon dioxide turns out not to be the boogey-man that climate scientists have made it out to be, tens of trillions will be wasted in unneeded remediation. Much of the world—billions of humans—will endure a severely diminished quality of life with nothing to show for it. The growth trajectory of the world in the twenty-first century may well depend more on the “truth” of climate change ex ante than ex post.
With climate change, as in many areas of scientific complexity, we can (and do) use models to understand the world. But models have their problems. This is particularly true when dealing with complex, non-linear systems with a multitude of recursive feedback loops, in which small variations produce massive shifts in the long-term outcome. Pioneered by the mathematicians Edward Lorenz and Benoit Mandelbrot, chaos theory helped explain the intractability of certain problems. Readers of pop science will be familiar with the term the “butterfly effect,” in which “the flap of a butterfly’s wings in Brazil set[s] off a tornado in Texas.” The earth’s climate is one such dynamic, chaotic system and it is within the whirling, turbulent vortex of unpredictability that the modern climate scientists must tread.
And boldly have they stepped into the breach. The scope of agreement achieved by the world’s climate scientists is breathtaking. To first approximation, around 97% agree that human activity, particularly carbon dioxide emissions, causes global warming. So impressed was the Norwegian Nobel Committee by the work of the Inter-governmental Committee on Climate Change and Al Gore “for their efforts to build up and disseminate greater knowledge about man-made climate change, and to lay the foundations for the measures that are needed to counteract such change” that it awarded them the 2007 Nobel Peace Prize. So many great minds cannot possibly be wrong, right?
Wrong.
So much of it is cross-discipline as well. Making ‘cycles of trust’ because paleodendrochronologists aren’t chemical or electrical engineers. Or atmospheric scientists. Though the modelling and statistics -should- be cross-discipline. But even there the true modellers are mostly comp-sci types – which is also disheartening.
Uh shut up. Only you and the other crazy people deny the obvious.
You’re proof of the old saying, “If a million people say a stupid thing, it’s still a stupid thing.”
The Earth’s climate has changed constantly thoughout geologic time and humans have only been around for a small percentage of that time.
We seem to have a new idiot troll.
Maybe I missed other comments from ian, but I’m assuming he intended sarcasm.
You missed other comments.
Yeah, now seeing it. Still, the comment is great parody. It has the typical, “because… shut up!”. It’s becoming the best retort Progressives have when confronted with real scientific analysis. And then the follow up, “deny the obvious” which references back to grasping at the consensus as the basis of empirical science, which of course is not science.
We used to have a consensus that the world was flat, and this belief was controlled by those ordained to be specialist in the matter. Those not ordained were derided as laypersons incapable of understanding the complexities of “real” science. Those laypersons were also told, and sometimes made to do so through violence, to Shut Up!
This is a perfect example of how the scientific method works. First, you begin with an anomalous result. Then you develop a hypothesis to attempt to explain that result. Then you tell everyone to shut up.
Then you publish the results in the prestigious consensus reviewed (peer review is old hat) journal “We’re Right, So Shut Up”. The great thing about publishing in this magazine is that you don’t have to worry about pesky researchers attempting to reproduce or invalidate your results. Just print it and forget it. Because shut up.
Someone brought up in comments the semantics games that often happen with this sort of false consensus. For me, it’s not particularly scientific to change definitions arbitrarily. For example, I’ve had people on the internet argue that “climate change” is somehow better scientifically than more accurate terms like “anthropogenic global warming”. One proponent even tried to claim that the term, “anthropogenic global warming” was a denialist bit of propaganda.
I think the most infamous example of this sort of thing outside of climatology is the redefining of Pluto as a “dwarf planet” back in 2006 by the International Astronomical Union. I’m still sore over the lousy justification for demoting Pluto and the weakness of the current definitions (such as, no definition for “clearing the neighborhood”, a “dwarf planet” isn’t a “planet”, and no applicability outside of the Solar System). But even stepping away from that, there isn’t really that much to gain scientifically from moving large Kuiper Belt objects from one category to another.
The more I read about scientific discoveries, the more I agree with the statement that scientific progress takes place when the old guard dies out. The use of Jupiter’s moon Io in the proof of light having a speed instead of instantaneous stands out.
Feynman on ‘Cargo Cults’. It brings to mind Dr. Mann’s own graduate student who re-examined the top two sets of proxies (and thus 70% of the weighting) of the Hockey Stick … and found neither to be correlated with temperature.
All experiments in psychology are not of this [cargo cult] type, however. For example there have been many experiments running rats through all kinds of mazes, and so on — with little clear result. But in 1937 a man named Young did a very interesting one. He had a long corridor with doors all along one side where the rats came in, and doors along the other side where the food was. He wanted to see if he could train rats to go to the third door down from wherever he started them off. No. The rats went immediately to the door where the food had been the time before.
The question was, how did the rats know, because the corridor was so beautifully built and so uniform, that this was the same door as before? Obviously there was something about the door that was different from the other doors. So he painted the doors very carefully, arranging the textures on the faces of the doors exactly the same. Still the rats could tell. Then he thought maybe they were smelling the food, so he used chemicals to change the smell after each run. Still the rats could tell. Then he realized the rats might be able to tell by seeing the lights and the arrangement in the laboratory like any commonsense person. So he covered the corridor, and still the rats could tell.
He finally found that they could tell by the way the floor sounded when they ran over it. And he could only fix that by putting his corridor in sand. So he covered one after another of all possible clues and finally was able to fool the rats so that they had to learn to go to the third door. If he relaxed any of his conditions, the rats could tell.
Now, from a scientific standpoint, that is an A-number-one experiment. That is the experiment that makes rat-running experiments sensible, because it uncovers the clues that the rat is really using — not what you think it’s using. And that is the experiment that tells exactly what conditions you have to use in order to be careful and control everything in an experiment with rat-running.
I looked into the subsequent history of this research. The next experiment, and the one after that, never referred to Mr. Young. They never used any of his criteria of putting the corridor on sand, or of being very careful. They just went right on running rats in the same old way, and paid no attention to the great discoveries of Mr. Young, and his papers are not referred to, because he didn’t discover anything about rats. In fact, he discovered all the things you have to do to discover something about rats. But not paying attention to experiments like that is a characteristic of cargo cult science.
Latest giggle-worthy attempt at sneaking garbage data into the accepted record:
Kaufman et al 2013 (PAGES)
Statistical rules for weeding outliers and determining suitability are for after you’ve weeded the obvious garbage. Of course Michael Mann did it first, second, and third – so it’s perfectly acceptable in “Climate Science”.
The biggest popular misconception about science is that it proves stuff. Science is all about disproving stuff.
Consensus is the antithesis of science. The lone disproof is the essence of science.
Those ‘scientist’ moving in herds mostly to gather funding are not good examples. The more they moo the less credibility they have.
Proof by authority has almost no weight with a true scientist (not to be confused with the crank that can not be persuaded by any facts.)
I think the usefulness of the K/C ratio will far outlive global warming theory if they can come up with some good, reliable metrics to gauge K and C. It would be useful in fields as diverse as economics and nutrition.
One indicator that global warming has a low K is that even if scientific journals added centerfold sections to accurately display the size of the error bars in an article’s predictions, real-world data still wouldn’t manage to land inside of them.
Too sleepy–I got to “even if scientific journals added centerfold sections” and figured the rest would be “they still couldn’t get anyone to read them.
Centerfolds? [Eyes darting around]