by Judith Curry
I am trying to understand how sceptics and warmists can look at pretty much the same information and come up with two very different conclusions - Mike Haseler, the Scottish Sceptic
I thought this would be a fun topic for this weekend – two different perspectives on what differentiates skeptics from non-skeptics/academics/warmists.
Skeptics vs academics
I am trying to understand how sceptics and warmists can look at pretty much the same information and come up with two very different conclusions and I have reach a stage I can tabulate some of my broader conclusions. I know this debate can get heated, but I honestly believe that on the whole both “sides” are trying their best to use their skills, training and experience on this complex problem.
I would very much appreciate your help and any views on this subject would be very useful. You can comment on the table in the article on my blog or by reply to this email.
He has a blog post sceptics vs academics, where he attempts to differentiate skeptics vs non-skeptics. I reproduce much of his post here:
This is part of a long term project to try to understand why the “two sides” in the climate debate look at pretty much the same information and come to very different conclusions. Having met both sides, and tried to understand their motivation and outlook, I am thoroughly convinced that both approach the subject in what they think is the right way and both are horrified at the “antics” of the other. If I have said anything that can be taken as derogatory, that was not the intention. I am sorry but I have done my best to describe what I see.
I WOULD VERY MUCH APPRECIATE COMMENTS FROM BOTH “SIDES”.
|Employment sector||Commercial & non-governmental||Academia, public sector & campaign charities|
|Employment||Electronic engineering, chemical engineering, energy engineering, general engineering, weather forecasting.||Environmental science, life sciences, climate science, civil service, journalism, campaign charities & general sciences.|
|Main focus||Prediction & hard facts.||Understanding & empathy.|
|Viewpoint||Individualistic, libertarian & conservative (not politically)||Public sector, Guardian liberal.|
|Viewpoint of Natural variation||Natural variation is around us everywhere and dominates natural systems.||Many things vary naturally and we capture these in our models. With enough data, measurement errors can be processed data so that we can ignore them.|
|Model of natural variation.||Measurement = Nat.Var.
after careful work …
f(t) + Nat.Var.(t)
Theory = Natural system.
|Main Expertise||Prediction, design & decision making||Theory, understanding and/or modelling through hindcasting. Communicating ideas.|
|Main Aim||Best decision||Best explanation|
|Attitude if prediction/model doesn’t match new data.||Poor quality like this cannot be tolerated by professionals. Good decisions require good models which include normal variation.
Those involved should sort the problem out or find another job.
|That is to be expected because this is how we improve our models.|
|Attitude if they don’t understand what is happening||Real life is like that and you learn to cope.||That is a dreadful admission. How can you say you can’t explain what is happening. A careless attitude like this cannot be tolerated.
Those involved should sort out their problems or find another job.
|Attitude to long term forecasting.||Forecasts get worse and natural variation increases the further away we try to predict from measured data.||Errors become smaller with more data so over the long term measurement errors can be ignored.|
|Extra discipline skill set.||Holistic, multi-skilled, complex, time & resource limited.
Includes practical economics, understanding how people react in real situations and how they reach decisions in the real world.
Used to complex systems with non-linear, non-deterministic behaviour, real time decision making, safety critical. Able to cope where there is not enough time or resources.
Focused on own area of expertise. Secure job with time to get to grips with subject. Reliant on peers to provide good data. Avoids messy, non-linear, non-deterministic systems operating in real time. Is almost never involved in commercial situations where there is too little time and resource (to involve academia).
|Problem solving approach||Bottom up
Start with the brass tacks facts, assess the situation to a professional standard & if there is time make make sense of it.
Start with the overall picture & fills in the details as understanding improves. Ignore all extraneous detail which cannot be modelled.
|Experience in decision making||Real time, high cost, critical to company’s survival and/or safety critical. Resource & information limited.||Which journal/newspaper to send latest work to?
What to do next to get next grant?
|What quality means||Getting it right first time||Work accepted by peers, newspaper, manager as “novel enough” & interesting enough for publication|
|Approach||What is normal and is there any sign of anything abnormal happening which requires attention?||How do we model the system and what do our models suggest will happen?|
|Basis for validation /falsification of hypotheses||Empirical data derived from real-time physical observations or reproducible experimentation.||Model simulations based on theoretical considerations supported by interpretations of selected paleo-climate proxy data|
Academics vs skeptics
For the flip side, here is a perspective from a non-skeptic academic: Stephan Lewandowsky. I cite here a Guardian article entitled Climate sceptics more likely to be conspiracy theorists and free market advocates, study claims. Excerpts:
If you answered yes to any of these conspiracy theories then a new study published today has found that you probably also think the science of human-caused climate change is some sort of hoax and you might think too that there’s no good evidence for vaccinating children.
The study, titled The Role of Conspiracist Ideation and Worldviews in Predicting Rejection of Science and published in the journal PLOS ONE, also finds another strong predictor for the dismissal of the science of human-caused climate change.
That is, if you’re a conservative who believes the world runs best when businesses operate in a “free market” with little government interference, then the chances are you don’t think human-caused climate change represents a significant risk to human civilisation.
The new study is led by Professor Stephan Lewandowsky, chair of cognitive psychology at the University of Bristol, and follows his previous study which caused the metaphorical head of the climate science denial blogosphere to explode.
Sceptics rejected Professor Lewandowsky’s initial findings largely because he had used questionnaires posted on climate blogs to gather the data.
None of those accusations can be used to criticise this new study, Professor Lewandowsky says, because the questionnaire was carried out by a third-party professional survey company using a sample that was representative of the US population. By email, he said:
There are some other more subtle differences, and despite all that, the results are pretty much identical: Free-market worldviews are strongly associated with rejection of climate science and conspiratorial thinking is associated with the rejection of all scientific propositions tested, albeit to varying extent.
This is a pervasive pattern now that has been shown multiple times in the literature by a number of different authors. I am now fairly convinced that wherever there is science denial, there is also a conspiracy theory waiting to be aired.
In the new study, which surveyed the views of 1000 people in the US, Professor Lewandowsky and his co-authors write that people’s worldview “constituted an overpowering barrier to acceptance of climate science”. Professor Lewandowsky told me:
I cannot be sure of the causality, but there are multiple lines of evidence that suggest that the involvement of worldview, such as free-market principles, arises because people of that worldview feel threatened not by climate change or by lung cancer, but by the regulatory implications if those risks are being addressed by society. Addressing lung cancer means to control tobacco, and addressing climate change means to control fossil-fuel emissions. It’s the need to control those products and their industries that is threatening people with strong free-market leanings.
Many “think-tanks” and organisations around the world which reject or underplay the risks of human-caused climate change do also advocate “free market” principles. Many have accepted funding from fossil fuel interests and rich conservative philanthropists.
But the research is careful to point out the findings don’t mean that conservatives are, by extension, more likely to exhibit “conspiracist ideation” which the study categorises as a style of thinking rather than a distinct personality trait.
But the study says the two groups do share a habit of engaging in what’s known as “motivated reasoning” – the tendency to accept without criticism any evidence that suits your belief while you ignore or reject the evidence that challenges what you think.
JC comments: I thought these two pieces were quite interesting when considered together. The skeptic (Haseler) digs in and really tries to understand the reasons why educated people look at the same evidence about climate change and come to other conclusions. The warmist (Lewandowsky) is looking to find evidence to support his ‘interesting’ ideas skeptics are conspiracy theorists, motivated reasoners, and something is wrong with their brains.
Help Mike Haseler with his study, discuss here and head over to his blog post for further details and discussion.