That was a wind up right? I sincerely hope so otherwise you have no sense of humour whatsoever.

tonyohagan, I must confess that if I was deluded enough to think that I was an expert in a field and that somehow that gave me authority over others and was likened to a monkey then I’d be a bit miffed just like you are. Thankfully although many people would call me an expert in certain fields e.g. web development, nuclear physics etc I am humble enough to admit that I am not, particularly given the subjective nature of who is or is not classed as an expert on a given subject. It’s all about who makes the judgement as to who is isn’t considered an expert. In this cas eit appears that you were the judge, so well done for picking a load of monkeys.

As Roger has more than adequately demonstrated in this case it matters not a jot whether you use a team of experts or a team of monkeys. In deference to and assuming that crc_fozzie’s post above wasn’t a wind up I assume that Roger didn’t in fact use monkeys so in this case no animals were in fact harmed as a consequence of his exercise (sorry WWF! you’ll have to get the money to save the soon to be extinct polar bears from someone else).

But on the other hand its no doubt nice work if you can get it I suspect (being chosen as an expert monkey that is!)

KevinUK

As more forests in western Africa are depleted to supply superfluous research, like yours, primate habitats shrink and their ranks come closer to extinction. Not only that, but the once verdant forests become stinking cesspools, ripe for the breeding grounds of malarial mosquitoes, contributing to countless more deaths and instability in that most troubled continent. And by depleting crucial natural resources because monkeys were absolutely crucial to your research, the countries of western Africa now have even less chance of recovering their economies and creating stable governments. This is assuming you used chimpanzees, as the photo you used implies.

Assuming you were using monkeys, as you say in the article, their origins were probably from the South American rainforest. By having to enter the rainforest in order to obtain monkeys for export, the suppliers helped contribute to the world-wide destruction of the rainforest. An ecosystem that once covered 14% of the earth is now cut down to a mere 6% and still declining. In the Amazon rainforest not only native animals and plants are losing their habitat, but also the native peoples. An estimated ten million Native Amazonians lived in that forest in the year 1500, but that number is now below 200,000. Yes, disease and colonization of the New World contributed to many of their deaths, but there were many tribes living in isolation in the rainforest until the rest of the world started destroying their home and displacing entire tribes. One would have thought we’d have learned from the mistakes of the conquistadors. Instead, people burn the trees in order to force the monkeys to flee their homes—right into the waiting traps of suppliers ready to export them to research facilities all over the world.

So next time, instead of trying to make a clever statement by comparing competent, educated scientists to monkeys, consider using a computer model. It could make the same point without the terrible costs.

Help support the World Wildlife Fund and end the use of animals in research:
http://www.worldwildlife.org/home.html

Let me now address Dr Pielke’s specific criticisms.

First, he says that the results obtained were indistinguishable from the results of randomly allocating weights between the various models, and he implies that this is inevitable. The latter implication is completely unjustified. I was not involved in the 2006 elicitation which Dr Pielke uses for his numerical illustration, but I can comment on the two most recent exercises. The experts were given freedom to allocate weights, and did so individually in quite non-random ways. In aggregate, they did not weight the models at all equally. The fact that the result came out in the middle of the range of separate model predictions in 2006 was therefore far from inevitable.

The elicitation exercise was designed to elicit the views of a range of experts. They were encouraged to share their views but to make their own judgements of weights. Dr Pielke says that the more experts we have, the more likely it is that the elicited average will come out in the middle, which is again fallacious. The result depends on the prevailing opinions in the community of experts from whom the participants were drawn. The experts who took part were not chosen by me or by RMS but by another expert panel. If, from amongst the models that RMS proposed, all the ones which would give high hurricane landfalling rates were rejected (and so given very low weights) by the experts, then the result would have ended up below the centre of the range of model predictions. The fact that it comes somewhere in the middle is suggestive, if it suggests anything at all, of RMS having done a good job in proposing models that reflected the range of scientific opinion in the field.

I think the above also answers Dr Pielke’s criticism of RMS’s potential conflict of interest. I agree that this potential is real. RMS is a commercial organisation and their clients are hugely money-focused. Nevertheless, as I have explained, the outcome of the elicitation exercise is driven by the judgements of the hurricane experts like Dr Pielke. Any attempt by RMS to bias the outcome by proposing biased models should fail if the experts are doing their job. If Dr Pielke is convinced, as he appears to be, that no model can improve on using the long-term average strike rate, then he could have allocated all of his weight to this model. That he did not do so is not the fault of RMS or of me.

This brings me back to the question of expertise. The elicitation was carefully designed to use to the full the expertise of the participants. We did not ask them to predict hurricane landfalling, which is in part a statistical exercise. What we asked them to do was to use their scientific skill and judgement to say which models were best founded in science, and so would give predictions that were most plausible to the scientific community. I believe that this shows full appreciation by RMS and myself of the expertise of Dr Pielke and his colleagues. For myself, the expertise that Dr Pielke seems to discount completely is based on familiarity with the findings of a huge and diverse literature, on practical experience eliciting judgements from experts in various fields, and on working with other experts in elicitation. In particular, I have collaborated extensively with psychologists and other social scientists. I don’t know how much Dr Pielke knows of such things, but to complain that what I do is “plain old bad social science” is an insult that I refute utterly.

Dr Pielke is no doubt highly-respected in his field, but should stick to what he knows best instead of casting unfounded slurs on the work of experts in other fields.

Chimpanzees, however, are better known for their cognitive research and numerical reasoning. They are social creatures that appear to be capable of empathy, altruism, self-awareness, cooperation in problem solving and learning through example and experience. Chimps even outperform humans in some memory tasks, as shown by Jane Goodall’s studies of chimpanzees in Gombe National Park in Northern Tanzania, starting in the 1960s.

See here for additional info

http://www.nytimes.com/2007/04/17/science/17chimp.html?ref=science

Good stuff. (As usual.)

But I think your picture may be of chimpanzees, rather than monkeys.

Here’s a good picture to use, the next time you write about expert panels of chimps:

http://www.solarnavigator.net/animal_kingdom/animal_images/Chimpanzee_thinking_poster.jpg

See:

http://sciencepolicy.colorado.edu/prometheus/evaluation-of-near-term-hurricane-loss-predictions-4800

I’m not either. Which is why I’m an AGW skeptic. Of course, I’m not a fan of Algore being used, either.