Communicating risk (Pt 3) – memes and the media

15/12/2009 — Leave a comment

The Newcastle 2007 storm

In part one and part two of this post I looked at Drew Warne Smith and James Madden’s article, “The science is in on sea-level rise: 1.7 mm”, in terms of it’s worth as a logical argument.

We live under a government of men and morning newspapers.

Wendell Phillips

While Smith and Madden’s argument turns out to be the usual denialist slumgullion it does serve as a useful jump off point for a discussion of the role of the media in propagating such pernicious memes (1) and more broadly in communicating risk.

Memes and the media

As proposed by Richard Dawkins a meme is a cluster of ideas which can be communicated from one person to another. Dawkins proposed the concept to explain how ideas propagate, using self replication, through a society and evolve in response to selective pressures. Looking at Smith and Madden’s piece as a ‘climate change denial’ meme we should ask what makes this meme, and other denialist memes more or less effective in both transmission and persistence?

In the old days men had the rack. Now they have the press.

Oscar Wilde

A useful way to analyse the spread of meme’s through a population is to treat the spread of meme’s as a ‘epidemic’ and use percolation theory to model the spread. In percolation theory a population is modelled as nodes networked together into clusters with infections travelling from node to node along the network links. The interesting thing about percolation theory is that it can explain (read model) how some epidemics neither burn out or flare up into a wildfire but instead persist in a chronic or low ‘brush fire’ level (2). In work done by Pastor-Santorras and Vespignani (2002) on computer virus propagation in scale free networks (3) the presence of a few nodes which are highly connected was found to ensure that an infectious outbreak did not burn out or flare up into an explosive growth phase but instead continued to persist at a low level (4).

So we can think of journalists Smith and Madden as highly connected nodes that once infected with a meme proceed to spread the meme broadly. Their action in continuing to transmit the denialist meme ensures that these memes persist, even in the face of apparently overwhelming evidence from the climate science community.

The media as high pass filter

A further problem with the media’s handling of risk communication is that it tends to act as a high pass filter where the most controversial claims are receive the greatest ‘column inches’ and are also most likely to be regurgitated on slow news days by editors (5). This process of filtering tends to propagate extreme views of risk and  anchor these extreme risk positions in the public consciousness. As most scientists are late to point out the worst case scenario (Type I error bias) this leaves the field open for the denials camp. The media also mediates risk messages through the interpretation of ‘balanced’ reporting requiring the reporting of both sides of any argument, regardless of the relative merits of either. This ‘equal time’ provides a competition damping mechanism that allows weaker meme’s to continue to compete with other meme’s regardless of their validity.

Adhocracy and pseudo-science

Another way in which the climate change denial meme increases it’s likelihood of propagation is that on the surface it appears to be ‘scientific’ in nature (7). This mimicry makes it difficult for those not trained in climate science or the scientific method to differentiate it from the mainstream scientific theory. This mimicry be seen as an adaptation of the meme that favours its survival, after all ‘climate change is wrong because we don’t like it as an article of faith‘ is unlikely to propagate much further than the darker corners of the interwebz.

A public heath response

The take-home from all this is that classical model’s of risk communication will be unlikely to be effective with what is such a highly politicised issue. Instead, much in the same way as the CDC deals with disease vectors in an epidemic, there needs to be a focused campaign to marginalise and neutralise (i.e. disconnect) the effects of the highly connected nodes espousing denialist rhetoric.

Notes

1.  In much the same way that a ‘selfish’ gene that acts to propagate itself Dawkins posited such cultural artifacts as melodies, catch-phrases, religious beliefs and technology use as potential memes.

2.  In classic epidemiological models, such as the SIR model, infections exhibit a threshold, below which they fizzle out and above which they turn into a full blown epidemic.

3.  A scale free network is one whose degree distribution (6) follows a power law, at least asymptotically. In succh a network there will be many nodes only connected to a few adjacent nodes, with a few that are highly connected.

4.  Interestingly in this model the blogosphere is not as important as some critics might belief as it is inherently ‘preaching to the converted’ and therefore connecting to a low number of ‘uninfected’. Such nodes, as with other marginal beliefs, serve more to reinforce the belief structure of members of the marginal group and preserve a reservoir of meme infection rather than to spread the meme further.

5.  A beautiful case study of this effect is the UK tabloid media’s reporting of the predicted number of cases of mad cow disease where early high side estimates (~800,000 – SEAC 1996 estimate) were re-reported on a regular basis even though other contemporary estimates were several order of magnitudes lower (<1,000 – Thomas & Newby 1996 estimate). Another importan point is that having reported the high side SEAC figure the media exhibited an amplification factor for the human risk heuristic of ‘anchoring’ where an initial estimate is favoured over contradictory later data.

6.  The degree of a node in a network is the number of connections it has to other nodes and the degree distribution is the probability distribution of these degrees over the whole network.

7.  One needs to carefully consider the methods used by the denialists to avoid being confounded by them. Like true science the denialists seem to be busy developing a complex theory that apparently fits the empirical evidence. Unlike true science the majority of efforts of the climate change denialists go into defending their theory. Normally they do this through ad-hoc amendments to their theories that circumvent the falsification of their theories by empirical evidence. But as Karl Popper has pointed out a theory that is not falsifiable is no theory, it’s an article of faith.

References

Dawkins, Richard (1989). The Selfish Gene (2 ed.). Oxford University Press. p. 186. ISBN 0-19-286092-5.

Pastor-Santorras, R.,Vespignani, A., Epidemics spreading in scale free networks, Physical Review Letters, 86, 3200-3203, 001.

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