How do scientists make judgments that require consideration of ‘the best available science’ under conditions of high uncertainty? To gain insight into this question, we surveyed a group of grizzly bear researchers. We found that the majority of experts recommended continued listing of bears, and that experts who were employed by state and federal agencies were 2-3 times more likely to recommend delisting grizzlies than their academic colleagues. This research is discussed in an article published today by The Conversation. You can also find a complete report of the project here.
Happy to see a post from JB!
Thanks Jeremy – in such cases of uncertainty (and they are legion) wouldn’t it be appropriate to properly apply (emphasis here) the precautionary principle or some version of it?
In decision theory, things like “precautionary principle” are supposed to be “baked in” to the calculation. It’s not a separate piece laying off to the side to fly in as a tie-breaker. It is part of the loss function (at least in the language I speak – Structured Decision Making might use another term, like “the objective function”).
We try to maximize the subjective expected utility (MSEU), as Savage taught us. The problem is we don’t agree on the SEU.
Thanks, JB: Beautifully written, as usual.
Well, one of the criteria for Delisting is an analysis of socioeconomic impacts. I guess ” Job Protection” fits that.
Less facetiously , it’s good to see this bias quantified. I’ve been saying as much for many a year, but could only claim it was anecdotal till now.