A massive problem in communicating the results of statistical calculations to the media and to the public is how we communicate uncertainty. Certainly most mass media seems to like a hard and fast number, even though except in a relatively small number of cases, numbers always have some uncertainty.
So, how can we, as statisticians (or scientists describing statistical work), best communicate our results, while keeping the uncertainty in tact, and making it meaningful to our audience?
I realise that this isn't actually a statistics question, rather a psychology question about statistics, but it's certainly something that most statisticians and scientists will be concerned about. I'm imagining that good answers might reference psychological research more than stats textbooks...
Edit: As per user568458's suggestion, a case-study may be useful here. If possible, please keep answers generalisable to other areas.
The particular case that I'm interested in serves as a nice example: the communication of climate science to politicians and the general public, through mass media. In other words, as a scientist, it is your job to convey information to a journalist in such a way that they have little difficulty in accurately conveying that information to the public - that is, the truth, although not necessarily the whole truth, which won't usually fit in a news-bite.
Some particularly common examples might be the communication of the uncertainty in the estimate of degree of warming over the remainder of the century, or in the increased likelihood of a specific extreme weather event (i.e. in response to a "was this storm caused by climate change" type question).