I really liked Robin's point that mainstream scientists are usually right, while contrarians are usually wrong. We don't need to get into details of the dispute - and usually we cannot really make an informed judgment without spending too much time anyway - just figuring out who's "mainstream" lets us know who's right with high probability. It's type of thinking related to reference class forecasting - find a reference class of similar situations with known outcomes, and we get a pretty decent probability distribution over possible outcomes.
Unfortunately deciding what's the proper reference class is not straightforward, and can be a point of contention. If you put climate change scientists in the reference class of "mainstream science", it gives great credence to their findings. People who doubt them can be freely disbelieved, and any arguments can be dismissed by low success rate of contrarianism against mainstream science.
But, if you put climate change scientists in reference class of "highly politicized science", then the chance of them being completely wrong becomes orders of magnitude higher. We have plenty of examples where such science was completely wrong and persisted in being wrong in spite of overwhelming evidence, as with race and IQ, nuclear winter, and pretty much everything in macroeconomics. Chances of mainstream being right, and contrarians being right are not too dissimilar in such cases.
Or, if the reference class is "science-y Doomsday predictors", then they're almost certainly completely wrong. See Paul Ehrlich (overpopulation), and Matt Simmons (peak oil) for some examples, both treated extremely seriously by mainstream media at time. So far in spite of countless cases of science predicting doom and gloom, not a single one of them turned out to be true, usually not just barely enough to be discounted by anthropic principle, but spectacularly so. Cornucopians were virtually always right.
It's also possible to use multiple reference classes - to view impact on climate according to "highly politicized science" reference class, and impact on human well-being according to "science-y Doomsday predictors" reference class, what's more or less how I think about it.
I'm sure if you thought hard enough, you could come up with other plausible reference classes, each leading to any conclusion you desire. I don't see how one of these reference class reasonings is obviously more valid than others, nor do I see any clear criteria for choosing the right reference class. It seems as subjective as Bayesian priors, except we know in advance we won't have evidence necessary for our views to converge.
The problem doesn't arise only if you agree to reference classes in advance, as you can reasonably do with the original application of forecasting costs of public projects. Does it kill reference class forecasting as a general technique, or is there a way to save it?
Your examples of "highly politicised science" are very one-sided (consider autism-vaccines, GM crops, stem cell research, water floridisation, evolution), which I suppose reinforces your point.
In your set-up, some reference classes correspond to systematic biases, and some to increased/decreased variance: they don't all change your probability distribution in the same way.
For example: it takes extreme levels of arrogance to conclude, in ignorance, that most scientists are incorrect on the area of their speciality. By this argument, you should place your own estimate of the most probable future course of the climate close to the scientific consensus (and the scientific consensus on global warming is pretty conistent). However, the science has been very politicised, so alternative theories may have been undermined; therefore your estimate can accept a large variance. "I agree with the scientific consensus, but tentatively", in other words.
Other example: doomseday-ee predictions. Overpopulation, peak oil, overfishing: in each case, the science in the prediction was pretty right. Population went up; there would have been peak oil with the methods of extraction of the time; fish stocks were destroyed. What was wrong was underestimating future progress and the ability of people to adapt to new situations. So scientific doomseday-ee predictions are a reference class with a special status: correct on their merits, incorrect on their supposed consequences.
So you've not to figure out which reference classes your issue belongs to, but also the type of that reference class, and its complete effect on your estimates.
I'd say reference class reasoning can be saved, but it's more of an art than an easily shared rational tool. If used honestly, you can get good information - but it's easy to abuse, and very unlikely to be convincing to others.
This is not what they were about. What they predicted was massive suffering in each case. Overpopulation doomsdayers predicted food and resource shortages, wars for land and water and such; peak oilers predicted total collapse of economy, death of over half of humanity, and such. Other than for their supposedly massive consequences peak oil is as interesting as peak typewriters, that is not at all unless you work i... (read more)