Politicized science

Tech Central Station piece on the political climate surrounding climate science.

The newspaper levels a serious charge - in effect that scientists were offered bribes by AEI. Any time a news organization levels an accusation this grave, it is incumbent upon it that the claims are fair and accurate. But the inaccuracies in this article appear right off that bat.

For starters, the article claims that AEI is a "lobby group." But it is no such thing. It is a research organization that is expressly prohibited by law from lobbying.

The author of the article, Ian Sample takes several quotes out of context. He claims the scientists were "offered... payments for articles that emphasise the shortcomings of a report from the UN's Intergovernmental Panel on Climate Change (IPCC)." I know many of the folks at AEI and write a column for a magazine they publish and was surprised to hear this charge. So I asked around and received a copy of the letter containing the offer. As it turns out, this claim is wildly off base.

The call for papers by AEI explicitly states that "The purpose of this project is to highlight the strengths and weaknesses of the IPCC process, especially as it bears on potential policy responses to climate change." Nowhere does Sample mention AEI asks participants to speak of the IPCC's strengths.

Sample also writes that AEI sought "essays that 'thoughtfully explore the limitations of climate model outputs.'" That makes it sound like they are offering money to undermine the IPCC's reliance on climate models. But in a letter to one of the scientists interviewed by the Guardian, the call for papers said "In particular, we are looking for an author who can write a well-supported but accessible discussion of which elements of climate modeling have demonstrated predictive value that might make them policy-relevant and which elements of climate modeling have less levels of predictive utility, and hence, less utility in developing climate policy." Sample does not mention the requests also sought to highlight the predictive value of the models. The letters are available online here and readers can assess them for themselves.