Classification of contrarian claims about climate change
The Argument Against Everything.
This recent paper examines the language used to argue against climate change. The authors developed a model to detect specific contrarian claims around climate change. To do so, they built a comprehensive taxonomy of contrarian claims. The process resulted in five major categories:
- It’s not happening.
- It’s not us.
- It’s not bad.
- Solutions won’t work.
- Climate science/scientists are unreliable.
Below is an example of how the sub-claims fell under the categories.
Next, the authors built a deep learning model to classify specific contrarian claims (Methods). From the paper,
The state-of-the-art pre-trained Transformer Language Model RoBERTA was employed to train another classifier using the Simple Transformers software package. RoBERTa is an optimized version of the popular BERT language model.
To examine the history of climate change contrarianism, the authors built a data set of 250+ thousand documents from conservative think tanks and contrarian blogs that span the last 20 years. This model was applied to the documents and annotated. The below shows the prevalence of the claims for the last 20 years.
So, the next step is very cool. Now, that the authors know who is talking about what topics. We can examine the funding of these think tanks and blogs and show what organizations are pushing what narrative.
Linear regression results show that the proportion of category 5 and category 1–3 claims are positively associated with the proportion of funding originating from these 10 key donors. Likewise, we find a negative association of category 4 claim prevalence with key donor funding. Figure 4d illustrates the sources of funding for 14 CTTs in our sample. Notably, prominent contrarian CTTs such as the Heartland Institute are heavily dependent upon these key donors and, in particular the “donor-advised” funding flows from Donors Trust and Donors Capital Fund, which ensure anonymous funding to conservative causes.