One of the major memes in the Global Warming camp is the 97% consensus of scientists. This number comes from one paper published by John Cook at Australia's University of Queensland about a year ago. Although the paper was publically funded, Cook has not released the raw data for other people to check his thesis.
Brandon Shollenberger has been curious about this and was able to find some data - the exact content is not known - publically available on a website. Now the University is trying to claim that Shollenberger 'hacked' into a secure server and is [threatening to sue](http://hiizuru.wordpress.com/2014/05/18/a-direct-challenge/) if the data is released.
Today, Brandon talks about [the definition of Consensus](http://hiizuru.wordpress.com/2014/05/20/a-re-analysis-of-the-consensus/):
> **A Re-Analysis of the “Consensus”**
Hey guys. I’ve been mulling over an idea I had, and I wanted to get some public feedback. What would you think of a public re-analysis of the Cook et al data set? > > A key criticism of the Cook et al paper is they didn’t define the “consensus” they were looking for. There’s a lot of confusion as to whether that “consensus” position is weak (e.g. the greenhouse effect is real) or strong (e.g. humans are the primary culprits). The reason for that is Cook et al tried to combine both definitions into one rating, meaning they had no real definition. You can see a discussion of that [here](http://rankexploits.com/musings/2013/climate-science-p0rn/). > > I think it’d be interesting to examine the same data with sensible definitions. Instead of saying there’s a “97% consensus,” we could say “X% believe in global warming, Y% say humans are responsible for Z% of it.” That’d be far more informative. It’d also let us see if rating abstracts is even a plausibly useful approach for measuring a consensus. > > My current thinking is to create a web site where people will be able to create accounts, log in and rate a particular subsample of the Cook et al data. I’m thinking 100 “Endorse AGW” abstracts to start with should be enough. After enough ratings have been submitted (or enough time has passed), I’ll break off the ratings, post results and start ratings on another set of abstracts. > > The results would allow us to see tallies of how each abstract was rated (contrasted with the Cook et al ratings). I’m thinking I’d also allow raters to leave comments on abstracts to explain themselves, and these would be displayed as well. Finally, individual raters’ ratings could be viewed on a page to look for systematic differences in views. > I love it -- crowd-sourced analysis. Bring it on!
Hey guys. I’ve been mulling over an idea I had, and I wanted to get some public feedback. What would you think of a public re-analysis of the Cook et al data set? > > A key criticism of the Cook et al paper is they didn’t define the “consensus” they were looking for. There’s a lot of confusion as to whether that “consensus” position is weak (e.g. the greenhouse effect is real) or strong (e.g. humans are the primary culprits). The reason for that is Cook et al tried to combine both definitions into one rating, meaning they had no real definition. You can see a discussion of that [here](http://rankexploits.com/musings/2013/climate-science-p0rn/). > > I think it’d be interesting to examine the same data with sensible definitions. Instead of saying there’s a “97% consensus,” we could say “X% believe in global warming, Y% say humans are responsible for Z% of it.” That’d be far more informative. It’d also let us see if rating abstracts is even a plausibly useful approach for measuring a consensus. > > My current thinking is to create a web site where people will be able to create accounts, log in and rate a particular subsample of the Cook et al data. I’m thinking 100 “Endorse AGW” abstracts to start with should be enough. After enough ratings have been submitted (or enough time has passed), I’ll break off the ratings, post results and start ratings on another set of abstracts. > > The results would allow us to see tallies of how each abstract was rated (contrasted with the Cook et al ratings). I’m thinking I’d also allow raters to leave comments on abstracts to explain themselves, and these would be displayed as well. Finally, individual raters’ ratings could be viewed on a page to look for systematic differences in views. > I love it -- crowd-sourced analysis. Bring it on!
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