6 Mar 2017

The Post-Truth Drift -- why it is partly the fault of Science (a short essay)

In a time which talks about being in a "post-truth" era of public discourse and where the reputation of "experts" as a group is questioned, it is easy to blame others for the predicament that Scientists find themselves (e.g. politicians, journalists, big business interests etc.). However, I argue that substantial part of the blame must fall on ourselves, the scientists  -- that we have (collectively), more than anyone, knocked away the pedestal on which they stood.

Firstly, scientists have increasingly allowed their work to be prematurely publicised - "announcing" breakthroughs with the first indicative results (or even before). It is, of course, understandable that scientists should believe in their own research, but it should be part of the discipline that we do not claim more than we have proved. Partly this is due to funding and institutional pressure, to quickly claim impact and progress (I remember an EU funding call that asked for "fundamental theoretical breakthroughs" and "policy impact" in the same project), but again it is part of the job to resist these pressures. More fundamentally, the basis for academic reputation has changed from cautious work to being first with new theories -- from collective to individual achievement.

The result of this over-hyping of results is that science loses its reputation for caution and reliability. This has been particularly stark in some of the "softer" sciences like nutrition or economics. All the clever mathematics in the world did not stop economists missing the last economic collapse - their lack of empirical foundations coming back to bite them. In the case of nutrition, a series of discoveries have been announced before their full complexity is understood.

However this goes a lot further than the softer sciences. The recent crisis in reproducibility in many fields indicates that publication has overtaken caution even for results that are not publicised outside their own field. This indicates that there is an imbalance in these fields with not enough people replicating and checking work and too many racing to discover things first. This is evident in some fields where there are a lot of researchers proposing or talking about abstract theories and not many doing the more concrete work, such as empirical measurement. Reputation should follow when an idea or model empirically checks out and not before.

Measuring academic reputation on citation-based indices reinforces this deleterious trend - one can get many citations for proposing an attractive or controversial idea, but it is independent of whether one was right or not. If we reward academics by their academic popularity with their peers rather than whether they were right, then that will affect the kind of academics we attract into the profession. Many fields are dominated by cliques who cite each other and (consciously or unconsciously) determine the methodological norms.

All fields need some methodological norms, however these norms can come about in ways that are independent of their success or reliability. Papers that grab a lot of attention can be more influential in these terms than those that turned out to be right. All fields seem to adjust their standards of success to ensure that the field, as a whole, can demonstrate progress and hence justify itself. When faced with highly complex phenomena, this can lead to a dilution of the criteria of success so this is achievable. In my field, abstract simulations without strong empirical foundations that provide a way of thinking about issues, gain more attention than they should and, more worryingly, are then advertised as able to perform "what if" analyses on policy inventions (implying their results will somehow correspond to reality). In economics, prediction rather than structural realism was declared as the aim of its modelling, but this weakened to predicting known out-of-sample data.

If all this weakening of criteria were internal and scientists were ultra-careful about not deceiving others into thinking their results were reliable, this would not be so bad. However, whether deliberately or otherwise, far too often the funders/policy makers/public are left with an impression that declared findings are more solidly based than they are. This is exacerbated by the grant funding process, where people who promise great results and impact are funded and more realistic proposals rejected. If one gets a grant, based upon such promises there is then pressure to justify outcomes that fall short of these, and to use language to obscure this.

Finally, when scientific advice and the policy world meet there is often fundamental misunderstanding, and this is partly the fault of the academics. In the wish for relevance and "impact" academics can be pressured into not being completely honest, and providing the policy makers with what they want regardless of whether this is justified by the science. One trouble with this interface is that there is not a clear line of responsibility -- if the advice from the scientists conflicts with those of the policy makers, what are they to do?  If they trust some complex process that they do not understand they are effectively delegating some of their responsibility, if they only trust it if agrees with their intuitions then this selection bias ensures that support rather than critique of decisions gets diffused.

The blurring of political and scientific debate that results from a non-cautious entry into policy debate has resulted in a conflation between debate over method and reliability of results to a confrontation of alternative results. Classically science has not debated results, but rather critiqued each other's method. If there are conflicting results this will not be resolved by debate but by further research. Alternative ideas should be tolerated until there is enough evidence to adjudicate between them. The competition should be in terms of sounder method, not in terms of which theory is better on any other grounds. Thus scientific debate has become conflated with political debate where, rightly, different ideas are contrasted and argued about.

There are some positive sides for science to the "post-truth" tendencies. The disconnected "ivory tower" school of research is rightly criticised. Whilst what academics do should not be constrained, what they use public money for has to be. The automatic deference that academics used to have from the public has also largely disappeared, meaning that results from scientists will be more readily questioned for its unconscious biases and meaning of its claims. To some extent the profession has become more porous with a wider range of people participating in the process of science - it is not just professors or boffins anymore.

Ultimately maintaining academic and research standards is the job of the academics themselves. The institutions they work in, the funders of research and the current governmental priorities mean that other involved actors will have other priorities. Universities compete in terms of the frameworks that government sets (REF, TEF etc.) or league tables constructed on simplistic indices. Funders of research are under pressure to claim research that has immediate and significant impact and publicity. It is only the academics themselves that can resist these pressures and so maintain their own, long-term reputations for independence and reliability. If we do not have these things, why should the public carry on financing us? What will people think of our science in 50 or 100 years time? Let the longer view prevail.

17 Feb 2017

Discussion paper: "Co-developing beliefs and social influence networks – towards understanding Brexit"

Centre for Policy Modelling Discussion paper: CPM-17-235


A relatively simple model is presented where the beliefs of agents and their social network co-develop. Agents can either hold or not each of a fixed menu of candidate beliefs. Depending on their type, agents have different coherency functions between beliefs, so that they are more likely to adopt a belief from a neighbour or drop a belief where this increases the total coherency of their belief set. With given probabilities links are randomly dropped or added but, if possible, links are made to a “friend of a friend”. The outcomes when both belief and link change processes occur are qualitatively different from either alone, showing the necessity of representing both cognitive and social processes together. Some example results are shown which moves a little towards modelling the processes behind divisive collective decisions, such as the Brexit vote.


15 Feb 2017

Slides from talk on "Simulating Superdiversity"

#cfpm_org #abm #ethnosim
An invited talk to the Institute for research into superdiversity (IRIS), University of Birmingham, 31st Jan 2017.

Abstract: A simulation to illustrate how the complex patterns of cultural and genetic signals might combine to define what we mean by "groups" of people is presented. In this model both (a) how each individual might define their "in group" and (b) how each individual behaves to others in 'in' or 'out' groups can evolve over time.  Thus groups are not something that is precisely defined but is something that emerges in the simulation. The point is to illustrate the power of simulation techniques to explore such processes in a non-prescriptive way that takes the micro-macro distinction seriously and represents them within complex simulations. In the particular simulation presented, groups defined by culture strongly emerge as dominant and ethnically defined groups only occur when they are also culturally defined.

Slides available at: http://www.slideshare.net/BruceEdmonds/simulating-superdiversity

Linked to the upcoming workshop on simulating ethonocentrism and diversity, Manchester 7/8 July 2017: 

3 Jan 2017

Sad to announce the death of my mother, Anne Gillian Edmonds ("Gill") 1935-2016

My mother died on the 24th of December, 2016. 

She was a loving and effective mother to us four (Bruce, Juliet, Nicola and Malcolm), encouraging us all to be creative, independent and care about social concerns. This little 'wave' of people continues with her grandchildren: Thomas, Ruth, Duncan, Orlanda, Patsy, Sophie, Ben, Iona, Kaila, and Joshua and great-grandchild, William.

As well as raising us mob, she pursued an active career as a social worker for Oxfordshire district council (and in the last couple of years of her work, the RAF). She was an active campaigner on Green and development issues, bombarding David Cameron (her local MP) with letters on these issues before he became PM.  She contributed actively to local life in Burford, volunteering her effort in many ways.

She was a relentless autodidact, achieving an open university degree whilst bringing us up, and continuing on a variety of courses until the very last years of her life.  She spent several years effectively looking after my father as his dementia progressed.

A funeral service will be held at St John the Baptist Church, Burford, on 14th January at 11.00 a.m. All welcome. (Family Flowers only)

5 Dec 2016

The international spread of nursing staff on my mother's ward

Where the nursing and assistant staff on my mother's hospital ward come from.  Only 7 out of about 40 come from the UK. If we restrict immigration of such staff our hospitals will collapse. This is not good for the countries they come from, but it undoubtedly benefits us. Note that many of them come from the EU, especially Spain and Portugal.