Tag: science

Categories
Research Social Sciences

What does a Pandemic mean for the social sciences?

A few months ago, I had the privilege of chatting with a student of public policy at one of the leading universities in the UK for science and disease. He was telling me about the postgraduate course he was on, and how public policy is a discipline based purely on science. I thought briefly, and then double checked. You don’t study anything resembling a social science at all then? No ethics, no law, no economics, for example? No no, public policy, he assured me, is based solely on scientific evidence.

I shelved my doubts and put any skepticism down to my natural bias as a social scientist and my tendency to argue for the wider understanding and valuing of the social sciences in any scenario.

And then COVID-19 happened. Of course, this is a scientific conundrum, and scientists, chemists, biologists, immunologists, epidemiologists, mathematicians, and the like are working together globally like never before to test, trial, model, and to keep the rest of us as safe as possible.

But then a strange thing happened. A trend appeared in the Covid19-related deaths, which, frustratingly has been inadequately recorded by the official statistics, but which is pretty plain to see on any photograph wall of “victims”. Deaths of those from a BAME, or those from a black or minority ethic background, exceed the numbers expected if these things were to be in proportion to the population. So what is going on?

A recent paper in The Lancet identified the issues surrounding ethnicity, stating “Ethnicity is a complex entity composed of genetic make-up, social constructs, cultural identity, and behavioural patterns.2 Ethnic classification systems have limitations but have been used to explore genetic and other population differences. Individuals from different ethnic backgrounds vary in behaviours, comorbidities, immune profiles, and risk of infection, as exemplified by the increased morbidity and mortality in black and minority ethnic (BME) communities in previous pandemics.” This can be represented in the following chart:

From Pareek et al, “Ethnicity and COVID-19: an urgent public health research priority”, available at https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(20)30922-3/fulltext

This “complex entity” of “ethnicity” straddles the natural and social sciences as well as the arts and humanities, and there has never before been such a huge need for the disciplines to work together. Could there be any correlation between being a front-line worker and BAME? Is there any truth in the statements that those from a minority ethnic background are more likely to live with extended family in smaller, more cramped housing? Or is the answer down to genetic susceptibility to co-morbidities? The research here is, surprisingly, still in its infancy, although projects like the UNESCO dialogue offer hope that society may be forced to confront the inequalities that COVID-19 has laid bare.

Once again, we are not all in this together. The virus is not a great leveller, and we are not all suffering equally. The statistics bear this out in black and white. But science can only carry us so far down the road investigating this. The rest must be in combination with the insights of lawyers, economics, psychologists, sociologists, anthropologists, and geographers, as well as historians, ethnographers, artists, musicians and – well, as much of society as possible if we really want a representative dialogue. And this means hearing voices that are usually silenced by inequality and minimised by power imbalances.

Interestingly, Germany may be already setting off down this road, enlisting scholars in the Arts and Humanities in that country to help establish a new normal and to ask how society can make sense of the changes. How can we forge meaningful relationships from a “socially-distant” 2 metres? And what might a post-COVID-19 society look like? Sound like? Behave like? Which social values and interests will be prioritised? These are questions that will require the full range of inputs, styles and learning from across the academy.

What is the new normal? And how do we figure out how to get there? This is something that will require the close cooperation of all disciplines.

Despite the fact that we are facing a viral enemy, arguably we have never needed interdisciplinary research more, specifically combining insights from the social sciences, arts and humanities to interpret, process, disseminate and enhance understanding of the work of the natural sciences. COVID-19 has highlighted inequalities that society had previously been able to ignore. The role of the social sciences, arts and humanities in elevating those voices and interests will be critical not only to the successful implementation of vaccines and treatments (community dialogue and involvement is essential for engagement with health services), but for the reconsideration of social priorities and equality more generally.

Categories
Visualising ESL

The Art of Innovation (Part 1)

There’s currently a very interesting exhibition on at the Science Museum in London called “The Art of Innovation”. It’s about the links and dialogue between the (natural) sciences and the arts.

Given my interest in the dialogue between the social sciences and the arts (have a scroll through some of the other posts in this blog if you’re new), the first part of the exhibition was a little wide of the mark. The artistic side of the first few exhibits included architecture, dress-making and textiles.

However the real showstopper for me was a piece designed by Theodore Olivier in 1830 (see below) in the section on “Meaningful Matter”. These were built to convey complex 3-dimensional ideas to a wide audience. The coloured strings could be adjusted using weighted beads in the frame, meaning that different surface shapes could be modelled according to the mathematical equation at question, revealing a number of surfaces and shapes simultaneously. These frames and models were eventually produced in significant numbers and sold across the world. The one in the picture below was made by French company Fabre de Lagrange.

Exploring surfaces and mathematical equations in 3 dimensions

However, as ideas progressed, these models fell out of favour with the mathematical and scientific communities. After the First World War, the models were displayed in museums as curios where they found a new audience; avant grade artists. The string models represented not the abstract thinking of the original mathematical equations, but the ability to explore shape and form in a new way.

Among those who drew inspiration from these models were Barbara Hepworth and Henry Moore. Hepworth modelled her sculpture on the mathematical models that she had seen at Oxford (see below).

Barbara Hepworth Sculpture inspired by mathematical equations
Barbara Hepworth sculpture inspired by mathematical equations

As a member of the St Ives set, it was therefore no surprise to see Hepworth joined on the opposite wall by a set of sketches by Henry Moore.

Sketches by Henry Moore
Henry Moore sketches inspired by equations

Moore’s sketches drew inspiration from the string recreations of maths equations that he encountered on display at the Science Museum when he was a student in the 1920s. Moore immediately recognised the structural and artistic possibilities the models presented, noting that “it wasn’t the scientific study of these models but the ability to look through the strings as with a bird cage and to see one form within another which excited me”. The sketches on display in the exhibition eventually inspired several wooden string figures of his own.

There are similarities with some of the work I’ve been doing with zentangling interaction patterns, as you can see in my previous posts. I’ve also built 3 dimensional string models using the colours of strings to represent economic, legal and “other” aspects of each interaction, overlapping these to build complex patterns. Some of the questions I’ve been pondering are how models like these could help us explore complex patterns of interaction in the context of the social sciences? How could we visualise economic and legal aspects of interactions using colour to build up overarching patterns of interaction?

Stay tuned for more from the exhibition in Part 2….

Categories
economics Research

The Science of Economics? What Works, and How Much…

We do seem to be talking more about economics – what it should do and look like. But there is still a whiff of revolution about calls for the discipline to be more evidence-based and, well, scientific. This article, by Philip Aldrick in the Times yesterday, argues for more careful scientific approaches, and this is worth noting. Of course, in the natural sciences, this would be taken as read. Drugs need to be extensively trialled before they are sold and used to treat disease in humans. But for some reason, in the social sciences, theory and ideology have the ability to shape policy just as much as evidence.

Aldrick’s piece cites two studies launched by Nesta, a UK Innovation think tank, roughly seven years ago. The first was a retrospective review of the effectiveness of business clusters; do small businesses do better when they are closely located and can share location and labour advantages? The second was a randomised controlled trial on whether tax relief for small creative companies worked. The results of the studies were not their most important findings however.

For the sake of finishing a story, the first study proved relatively inconclusive, and could not find any clear correlation between clusters and growth. The second study found that tax and financial incentives were helpful in the short term for small creative businesses, but after 12 months any advantage had faded.

So, what was the main impact? The reason these two studies are remarkable are for their illustration of research methods. While retrospective reviews – generally the majority of most empirical work in the social sciences – can only look for correlation, randomised controlled trials (RCTs) can go deeper, further, and can identify causative factors. In other words, we can target specific factors and identify why things happen. This is important because it means we can be more scientific about what works, how it works, and why. And this means we can begin to base policy on evidence rather than theory. RCTs also offer a way of measuring the extent of policy impacts. By having a test group and a control group, we can gauge the extent to which a policy really makes a difference. And that means we can evaluate whether a policy is financially and economically viable. So, RCTs offer a way of seeing not only what works, but how much.

Why is this news? Similar to other recent posts on here, there is increasing discussion of economics and how the discipline can be improved in the mainstream media. Aldrick’s argument is that economics – both the research and the formulation of policy – can and should be more scientific in its approach. And to this end he calls for more RCTs and longer term studies testing causation before policy is enacted. The government has launched the Business Basics Fund with Nesta to carry out trials investigating, among other things, productivity. UK productivity lags behind that of other countries, attributed generally to poor management practices. But how can management practices be altered to improve productivity?

Questions like this lend themselves readily to RCTs where different techniques can be trialled in comparison with a control group. Nevertheless, there are questions of macroeconomics that are not suitable for trials. We cannot test interest rates or tariffs, for example, against control groups. And this remains a problem for the larger questions tackled in macroeconomics, where theory remains a significant influencer of policy.

Calls for greater use of careful empirical data in shaping economic, legal and social science policy is not new though. Economic sociology, economic sociology of law, and sociolegal approaches have long stressed the need for analysis and understanding to be based firmly in the real world, on real data, and about real people. Increasing access to big data and AI could enhance this. As Aldrick states, “Economics is a social science. Why not make it more scientific?”