Via a link from InstaPundit, here is an eye-opening article from the current issue of Wired: “Accept Defeat – The Neuroscience of Screwing Up“:
Kevin Dunbar is a researcher who studies how scientists study things — how they fail and succeed. In the early 1990s, he began an unprecedented research project: observing four biochemistry labs at Stanford University.
… Dunbar brought tape recorders into meeting rooms and loitered in the hallway; he read grant proposals and the rough drafts of papers; he peeked at notebooks, attended lab meetings, and videotaped interview after interview. He spent four years analyzing the data. “I’m not sure I appreciated what I was getting myself into,” Dunbar says. “I asked for complete access, and I got it. But there was just so much to keep track of.”
Dunbar came away from his in vivo studies with an unsettling insight: Science is a deeply frustrating pursuit. Although the researchers were mostly using established techniques, more than 50 percent of their data was unexpected. (In some labs, the figure exceeded 75 percent.) “The scientists had these elaborate theories about what was supposed to happen,” Dunbar says. “But the results kept contradicting their theories. It wasn’t uncommon for someone to spend a month on a project and then just discard all their data because the data didn’t make sense.”
You really need to read the rest, because it provides a fascinating insight into the frustrations encountered by research scientists on a regular basis. I spent the better part of a decade working in a testing and analysis laboratory. We never did “pure research” — all of our work was based on well-known analysis methods and verified by standard quality control procedures. Still, we occasionally had to re-do entire sets of tests if our quality controls indicated errors. Researchers can sometimes trace unexplained results back to commonly encountered problems with laboratory equipment, reagents, or calibration standards, but many times there is no clear understanding of why the results of carefully planned experiments end up being “wrong.”
The Instapundit reader who emailed this story to Glenn Reynolds wryly noted, “Wired Magazine unknowingly explains Climategate.” How true. As I have previously noted, the ClimateGate scientists, most notably Michael Mann and Phil Jones, seem to have fallen prey to the temptations of celebrity recognition and unlimited research funding that are promised by those in power when scientific research seems to be producing the “right” answers. Mann, Jones, et. al. undoubtedly believed that they were on to something significant, but chose to disregard objectivity when confronted with the fact that much of their research data apparently resided in that damnable 50% – 75% category of errant or unexpected results.
Those data problems forced the AGW scientists into a “publish or perish” dilemma because so many people desperately needed their research to confirm the “truth” of AGW. In particular, leaders of Second and Third world nations, empowered by the UN and tired of perpetually lagging behind the West economically, needed AGW because it was their best hope for slowing down the economic growth of the West, thereby relatively increasing their own economic power.
Thus the AGW researchers were forced to find creative methods of fudging data in order to hide problems and produce the results that the UN expected to see. But it wasn’t just about politics — the “right” results would also guarantee a lifetime of unlimited research funding by those who stood to profit from cap and trade schemes, carbon credits, and other solutions aimed at “fixing” AGW. With so much at stake, fudging the data became the only logical option. They also took their deception a step further when they attempted to rig the peer review process in their favor by packing peer review boards and blackballing journals that published research that contradicted theirs.
The next time you hear someone claim that “the science is settled” with regard to climate change, ask them to explain how the climate change gurus dealt with the 50% to 75% of their data that was probably inexplicable or unusable. Their stunned response should be the only rebuttal you’ll need.
UPDATE 12-30-09: I did a bit of re-writing in order to clarify some thoughts and to include something I had inadvertently omitted, which was the corruption of the scientific peer review process by Mann, Jones, et. al.
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Climategate jolted me into confronting the massive fraud and deception by top global warming scientists, who were in a position to twist the peer-review process in their favor, and did so shamelessly.
Yet still most media reports desperately minimize Climategate, saying that it doesn’t taint the massive research supporting global warming theory. To them I say, how do you know that? Have you investigated how much of that research was published due to the manipulation of these unethical and fraudulent scientists? Do you know how much research that goes against the global warming activist claims was unfairly suppressed?
Until all this is known, it’s not possible to say with any confidence how much of global warming theory will remain after all the fraud and deceit has been removed.
• Global temperature changes naturally all of the time, in both directions and at many scales of intensity.
• The warmest year in the U.S. in the last century was 1934, not 1998. The U.S. has the best and most extensive temperature records in the world.
• Global temperature peaked in 1998 on the current 60-80 year cycle, and has been episodically declining ever since. This cooling absolutely falsifies claims that human carbon dioxide emissions are a controlling factor in Earth temperature.
• Voluminous historic records demonstrate the Medieval Climate Optimum (MCO) was real and that the “hockey stick” graphic that attempted to deny that fact was at best bad science. The MCO was considerably warmer than the end of the 20th century.
• During the last 100 years, temperature has both risen and fallen, including the present cooling. All the changes in temperature of the last 100 years are in normal historic ranges, both in absolute value and, most importantly, rate of change.
You’ll want to make sure you read all of this one.