Commentary in Psychological Science

This is a joint post by Ruth Dixon and Jonathan Jones about our Commentary entitled ‘Conspiracist Ideation as a Predictor of Climate Science Rejection: An Alternative Analysis.’

After nearly a year, two journals, and four rounds of review, our Commentary on two studies by Stephan Lewandowsky was published in Psychological Science on 26 March 2015. This post describes our findings in more detail than the tight word-limit in Psychological Science allowed.

In two papers published in 2013, Stephan Lewandowsky and his colleagues Gilles Gignac and Klaus Oberauer suggested that ‘conspiracist ideation’ (the tendency to believe in conspiracy theories) predicted scepticism about anthropogenic climate change. In our reanalyses of the data from both studies, we found that there was a curved relationship between these variables. Both climate-change sceptics and the ‘climate-convinced’ tended to disbelieve in conspiracy theories. The linear models used by Lewandowsky and colleagues were therefore not appropriate descriptions of the data. Both datasets show this effect, although they resulted from very different survey types (the first surveyed readers of ‘climate blogs’ (LOG13-blogs, published in Psychological Science) and the second surveyed a panel representative of the US population (LGO13-panel, published in PLoS)), so we are confident that our findings are robust.

As we describe in more detail later in this post, our main finding was that there is a curved relationship between belief in anthropogenic climate change (CLIM) and belief in conspiracy theories (CY). This curvilinear relationship is most clearly seen in the LGO13-panel dataset (Figure 1).

Figure 1. The curved relationship between belief in anthropogenic climate change (CLIM) and in conspiracy theories (CY) (Loess plot, 95% confidence intervals). Higher values correspond to higher levels of belief or endorsement.

Figure 1. The curved relationship between belief in anthropogenic climate change (CLIM) and in conspiracy theories (CY) (Loess plot, 95% confidence intervals). Higher values correspond to higher levels of belief or endorsement.

As we argue below, all this really shows is that people who are undecided about one fairly technical matter (conspiracy theories) also have no firm opinion about another (climate change). The complex statistical models used by Lewandowsky et al. mask this rather obvious and uninteresting finding.

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How Many Judicial Review Cases Are Received by UK Government Departments?

During the debate in parliament on Monday 1 Dec 2014, Chris Grayling (Lord Chancellor and Secretary of State for Justice) was asked how many Judicial Review cases are brought against government ministers.

Julie Hilling (Bolton West) (Lab): The right hon. Gentleman says “all the time”. Will he give us a notion of how often that is—once a day, once a week, once a month? How many times have such cases happened since April, for instance? He is giving the impression that they happen all the time, but what does that mean?

Chris Grayling: A Minister is confronted by the practical threat of the arrival of a judicial review case virtually every week of the year. It is happening all the time. There are pre-action protocols all the time, and cases are brought regularly. Looking across the majority of a Department’s activities, Ministers face judicial review very regularly indeed. It happens weeks apart rather than months apart.

The minister gave no actual numbers in his answer. So, in this post I’ve looked at how many judicial review (JR) cases were received by central government departments (‘ministers’) over the past few years. This analysis relates to my work with Christopher Hood in the Politics Department at Oxford.

There is a good discussion of the wider issues raised by Chris Grayling’s responses during that debate by Mark Elliot on the Public Law for Everyone blog. In this post I just look at the numbers. Continue reading

Circles and Squares – Where Do the Facts Lie?

I enjoyed the conference, ‘Circling the Square’ (20-22 May 2014) organised by Reiner Grundmann and colleagues from the Science,Technology and Society Priority Group at Nottingham University. Bringing together academics from the natural and social sciences (and others), the conference explored how scientific knowledge is (or should be) used for policy. Some reactions have been collated by Brigitte Nerlich on the Making Science Public blog.

There were many facets to the discussion, but here I will make just a few observations. As a former natural scientist now attempting to become a social scientist, I appreciated the refreshingly frank (and generally good-natured) exchanges on the different world views across the natural/social science divide (or continuum).
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