I can imagine a sort of selection bias in the grant process. I cannot imagine hundreds of scientists thinking, well, I put ten years into getting my PhD–time to spend the rest of my life faking data in order to get some grant money! One, yes. All of them, no.
To me, the worry is the subtler kind of bias that we indisputably know has led to scientific errors in the past. Richard Feynman has the most elegant exposition I’ve ever read:
We have learned a lot from experience about how to handle some of the ways we fool ourselves. One example: Millikan measured the charge on an electron by an experiment with falling oil drops, and got an answer which we now know not to be quite right. It’s a little bit off, because he had the incorrect value for the viscosity of air.
… Why didn’t they discover that the new number was higher right away? It’s a thing that scientists are ashamed of–this history–because it’s apparent that people did things like this: When they got a number that was too high above Millikan’s, they thought something must be wrong–and they would look for and find a reason why something might be wrong. When they got a number closer to Millikan’s value they didn’t look so hard. And so they eliminated the numbers that were too far off, and did other things like that.
… The first principle is that you must not fool yourself–and you are the easiest person to fool. So you have to be very careful about that. After you’ve not fooled yourself, it’s easy not to fool other scientists. You just have to be honest in a conventional way after that.
That is the actual worrying question about CRU, and GISS, and the other scientists working on paleoclimate reconstruction: that they may all be calibrating their findings to each other. That when you get a number that looks like CRU, you don’t look so hard to figure out whether it’s incorrect as you do when you get a number that doesn’t look like CRU–and maybe you adjust the numbers you have to look more like the other “known” datasets. There is always a way to find what you’re expecting to find if you look hard enough.
There are other issues: selection bias in the grant process, papers with large results being much more likely to be published than papers with equivocal results, professors preferring students who agree with them, and so forth. I doubt that could amount to faking the entire thing. But it could amplify the magnitude.
Like Ms. McArdle, I happen to disagree with those who infer from the recent “Climategate” emails that the CRU team was deliberately “faking” or “falsifying” their data. It is much more likely that they were routinely performing seemingly innocent data massaging in order to move their results toward an outcome that was assumed beyond question to be correct.
This type of bias does not discriminate. Even the greatest scientific minds have been hindered in both their theoretical and experimental work because their initial assumptions were wrong.
A little over a century ago, Albert Einstein published a short paper with the rather uninteresting title “On The Electrodynamics of Moving Bodies.” Einstein was intrigued by the persistent problems that were caused by the conflict between Maxwell’s theory of electromagnetism and Newton’s laws of motion. Building on the work of Lorentz and others who were also working on the same problem, Einstein proved conclusively that the speed of light was a constant, while it was distance and time (erroneously assumed by Newton and everyone else to be universally constant) that changed, from the point of view of one observer to another, when one of those observers was traveling at a velocity near the speed of light. From this work, Einstein also derived his famous expression e = mc2, which showed that energy and mass were equivalent, related to one another by the speed of light. Einstein’s discoveries were astounding, and they literally changed the way physicists understood nature.
Ten years later, Einstein published his greatest comprehensive work, General Relativity, which took his newly-discovered relationships between mass, energy, and the speed of light, and applied them to the universal (or “general”) phenomenon of gravitation, which was the cornerstone of Newtonian physics. The mathematical models that came out of General relativity predicted a number of surprising phenomena including black holes and gravitational waves, and something that greatly troubled Einstein himself: an expanding universe.
Ever since the dawn of time, mankind had assumed that the size of the universe as a whole was static. Individual bodies moved in orbit and interacted with one another through the effects of gravity, but the spatial dimension of the universe did not change. That was simply a given. An expanding universe was an absolute impossibility, and therefore must be the result of a mathematical error. In order to correct this error, Einstein introduced a “fudge factor” that he called the Cosmological Constant into his equations. The Cosmological Constant eliminated the expansion and gave the “right” result, a stationary universe. After astronomer Edwin Hubble found conclusive observational evidence for an expanding universe, an embarrassed Einstein admitted that introducing the Cosmological Constant had been the “biggest blunder” of his career.
Today, none of us would vilify Einstein as a “liar” or the perpetrator of a hoax. We recognize that he simply attempted to correct his work it in what he assumed was an appropriate manner, given the prevailing assumptions of his day. Similarly, the climate scientists at East Anglia’s CRU worked very hard to figure out why their measured data was not corresponding to their own prevailing assumption that the climate had experienced a steep warming trend since the beginning of the twentieth century. Their solution to the problem was to adjust the data in order to obtain the “right” result. A conspiracy of sorts perhaps, but probably not a deliberate or malicious one.
Einstein admitted his error, and history exonerated him; it remains to be seen if the CRU team and other climate change proponents will admit to the ideological biases that we now know resulted in sloppy record keeping, questionable statistical methods, and apparently deliberate attempts to silence critics. With billions, perhaps trillions of dollars at stake in the climate change debate, they owe it to us to come clean.