It has been a long time that I read something of John Cook. I recently came across the National Center for Science Education blog post in which he was interviewed. The post is titled Got Climate Change Misconceptions? John Cook Can Help and dates from the beginning of this year. This “help” seems to be learning students how to combat climate change misconceptions.
I am not going to make a long post, so I will come to the point immediately. This is what caught my eye at first read (my emphasis):
Another term that I recently learned is “False Equivalence” (when two things are proposed as being equal, although there are substantial differences between the two). Reading the Skeptical Science article “97% consensus on global warming” that I discussed in previous posts, I spotted one right away. It is the good ol’ doctor’s analogy.
This is how it is explained in the article:
Expert consensus is a powerful thing. People know we don’t have the time or capacity to learn about everything, and so we frequently defer to the conclusions of experts. It’s why we visit doctors when we’re ill.
Which is all true. Expert consensus is indeed a powerful thing. It is also true that people are not able to learn about everything and, in things we don’t know much about, we turn to people who (seem to) know more about it. One such example is going to a doctor when being ill. Not everybody is able to get a degree in medical science, so when we feel ill, we turn to those people who got such a degree. For the record, I will happily go to a doctor when I am ill, knowing that medical science, while not perfect, is rather reliable and if I listen to the advice of the doctor, chances are that I get well again.
My eyes started to roll when the author of the article states that:
The same is true of climate change: most people defer to the expert consensus of climate scientists.
In previous post, I discussed a graph that suggested that the CO2 and CH4 levels in the atmosphere are unprecedented in the last 800,000 years and proposed that it is misleading to compare high resolution data with low resolution data. After I published that post, I wondered whether I could illustrate this with an example. It should be possible if I had some detailed dataset. Then I could make a detailed graph, see how that looks like, then sample this dataset in the same way as a proxy dataset and again make a graph. Comparing both graphs should make clear what the effect is.
There is this statement in the introduction of the Cook et al 2018 paper that caught my eye:
This paper introduces key critical thinking concepts and outlines a straightforward process for identifying reasoning errors that allows for people who lack expertise in climate science to confidently reject certain denialist arguments.
In a way, I can understand what they are trying to do. Just before I started blogging, now five years ago, I had the idea to look somewhat deeper into logical fallacies. At that time I wasn’t familiar with the global warming debate and it was my hope that I could find a fast and easy way to differentiate between right arguments and wrong arguments, without having to put much effort in studying the topic. However, it didn’t take very long before I realized that for some type of fallacies this would be perfectly possible, but not for most. If I wanted to know right from wrong, then I had to dive in the arguments themselves.
So although I think that their effort is praiseworthy, in practice it is not black & white. My conclusion back then was that when one wants to confidently confirm or reject an argument, then one needs to get messy and go to the source and understand what the argument is all about. I would certainly not put my bet on the knowledge of logical fallacies alone. Without some background, it could lead to possible misinterpretations.
This became rather clear in the page on the SkepticalScience website that was devoted to the Cook et al paper. The post is titled Humans need to become smarter thinkers to beat climate denial and John Cook is a co-author. At the beginning of the post, they basically repeat the statement from the paper in a slightly different wording:
Spread over the Cook et al 2018 paper are the terms “anthropogenic climate change” and “anthropogenic global warming”. It is also mentioned a in table S2 of the supplementary material. I assume that “anthropogenic global warming” means that global temperatures are rising and humans have an impact. This seems to be supported by the consensus claim from the paper (my emphasis):
There is an overwhelming scientific consensus that humans are causing global warming (Cook et al 2016), with a number of studies converging on 97% agreement among publishing climate scientists or relevant climate papers (Doran and Zimmerman 2009, Anderegg et al 2010, Cook et al 2013, Carlton et al 2015).
That is a far cry from the previous statement in the Alice in Wonderland paper. In that paper, the claim was made that there is a consensus that global warming “presents a global problem”. A claim that obviously was unsupported by the papers that were referenced.
At least he skipped the “dangerous” part of the claim. It is now in line with what the referenced papers researched. As explained in the link above, the referenced papers investigated the claim that global temperatures are rising and that humans have an influence in this. Not whether it is dangerous. Not whether something should be done about it.
However, I don’t think that the term “AGW” is used in this way in the paper. This sentence in the abstract makes me think that he means something different (my emphasis):
When I read the new Cook et al 2018 paper for the first time, the one thing that stood out was that the example arguments were simplified versions of skeptical arguments, stripped down of any nuance and context, therefor not representative anymore. I already foresaw many posts in my future about these fabrications…
In the meanwhile I found the discussion of Barry Woods on Twitter, tirelessly calling out the many misrepresentations in the paper. The reaction of some of his opponents, that this doesn’t matter because the compiled arguments are fallacious anyway, puzzled me. I couldn’t grasp that they were just okay with:
- The authors (or Cook and the SkS team) coming up with simplified, unnuanced arguments based on what they think their opponents believe
- then Cook et al show that these simplified, unnuanced arguments are logically fallacious
- thus providing proof that their opponents are wrong and therefor should be safely ignored when it comes to those issues.
That is about as close as one can get to a straw man argument. For those who are not familiar with this type of fallacy, according to wikipedia the definition of a straw man argument is (my emphasis):
A straw man is a common form of argument and is an informal fallacy based on giving the impression of refuting an opponent’s argument, while actually refuting an argument that was not presented by that opponent.
The examples Cook et al used were textbook examples of this type of argument, but the defenders of the paper were undeterred by it or maybe did not understand the concept. It seemed to shed of them like water off a duck’s back. I couldn’t really understand that, given that it is pretty clear for everybody to see.
Until I found following tweet:
In the beginning of this month, the new paper of Cook et al (John Cook et al 2018 Environ. Res. Lett. 13 024018) was published. I was quite busy around that time, so it was only when I was finalizing my last post that I suddenly realized that I didn’t have a look at it yet. Time to finally read that paper.
The paper is titled “Deconstructing climate misinformation to identify reasoning errors” and there is also a video abstract in which the approach of the paper is explained in very simple terms. Although I am not that keen on watching videos, I gave it a try.
Screenshot of the abstract video Cook et al 2018 paper
Having read the paper in the meanwhile, the video illustrates perfectly the strength and the weakness of the paper.
Let us first look how the story goes.