Nothing.
For a number of reasons that we have already expressed, we are highly skeptical of various hypotheses and theories that attribute historical changes (increases) in temperatures to human development and extrapolate continued changes (again, read increases) in temperatures to people.
We’d prefer that climatologists get a better understanding of the effects on earthly temperatures of solar flares, sunspots, and solar winds as well as the cyclic variations in the earth’s axis (tilt) before prescribing actions to try to mitigate the effects of using the air conditioning or driving the Suburban.
To us, the whole thing smacks of anti-humanism and reminds us of the first Star Trek movie. (You know: the one where V-ger wants to eliminate the carbon-based units (people) that (who) are infesting (operating) the starship, Enterprise–the one in which the main characters look kind of old, rather than the subsequent ones in which they look very old.)
But that’s not why we are writing today. No, we’re trying to make a larger point.
Skepticism: what is it good for?
During the past week, there has been much press coverage of the contents of various e-mails among academic believers in “global warming.”
The e-mails illustrate that both message writers and receivers have their own agendas, and they won’t necessarily let facts stand in the way of their stories and recommendations.
Thus, the “researchers” come across as biased, petty, vindictive, reflexive, scheming, and closed-minded to empirical results that don’t support their positions.
We’re sure the above characterization is true, but we wonder what distinguishes those global warming proponents from researchers in any other field?
Our answer: nothing but the topic. Show us a group of carbon-based units pushing (supplying evidence to support) a particular hypothesis (perspective or viewpoint), and we’ll show you a biased, petty, vindictive, reflexive, scheming, and closed-minded lot.
Do we expect (or demand) “scientists,” “researchers,” or academics to be anything else?
No, we expect them to be fallen and human–just like us. (Perhaps, on average, not as good-looking, but otherwise, not much different.) We’d go as far to argue that anyone who claims otherwise–that they are only seeking the truth–is either a liar or doesn’t accomplish much: the former because any research design involves any number of subjective choices and assumptions that (by definition) depend upon the person’s biases and perspective and the latter because no matter how one tries to generalize the problem to remove such choices and assumptions, it is impossible. However, that generalization process tends to take a lot of time and energy to (attempt to) do.
By the way, we definitely believe that truth exists, but we don’t think that humans are perfect arbiters of it; we’re not that presumptuous so we’ll leave that role to God.
Our point is that not only should one be skeptical of global warming “research” results but one should be skeptical of all research. Historically, much that was thought to be known has been discarded: phlogiston and caloric theory anyone? Medical research, social science research? Ever hear of errors in those fields? No? Then you don’t pay much attention.
To be clear, we are not arguing that all such research and investigation is worthless–just most of it. The problem is that one cannot be sure what is worthless and what is not until the project is completed, or, in fact, sometimes not for many years afterwards.
So, we have no problem with the proverbial equivalent of millions of blind monkeys randomly pounding away on their keyboards–each one trying to write a masterpiece in their field of study.
Just remember that regardless of the random outcomes, each of those “monkeys” has its own biases and prejudices, and there is a very good chance those very human and inherent factors affect how the “monkeys” view their own output and the output of others.
P.S. We recall being at an academic seminar where a very silly regression “model” was presented: one of many such sessions that we attended during our academic career. The variables of interest clearly depended upon one another. We explained that OLS (ordinary least squared) regression was inappropriate model because there was no independent variable and the inter-relationships must be considered when attempting to measure the effect of one variable on another. All the variables were endogenous. The presenter replied that others had used the same (flawed) method on the same topic; so, they were just following a well-established line-of-research. There’s no way to argue with the level of disingenuity and stupidity. (Monkey see, monkey do.) Situations like that, along with similar examples in the corporate world, were the impetus for our firm’s motto, thought before calculation.
