research
My experience with geopolitics of knowledge in political philosophy so far
Geopolitics of knowledge is a fact. Only few (conservative) colleagues would contend otherwise. Ingrid Robeyns wrote an entry for this blog dealing with this problem. There, Ingrid dealt mostly with the absence of non-Anglophone colleagues in political philosophy books and journals from the Anglophone centre. I want to stress that this is not a problem of language, for there are other centres from which we, philosophers from the “Global South” working in the “Global South”, are excluded. In political philosophy, the centre is composed of the Anglophone world and three European countries: Italy, France, and Germany. From my own experience, the rest of us do not qualify as political philosophers, for we are, it seems, unable to speak in universal terms. We are, at best, providers of particular cases and data for Europeans and Anglophones to study and produce their own philosophical and universal theories. I think most of you who are reading are already familiar with the concept of epistemic extractivism, of which this phenomenon is a case. (If not, you should; in case you don’t read Spanish, there is this).
Critical political philosophy is one of the fields where the unequal distribution of epistemic authority is more striking. I say “striking” because it would seem, prima facie, that political philosophers with a critical inclination (Marxists, feminists, anti-imperialists, etc.) are people more prone to recognising injustice than people from other disciplines and tendencies. But no one lives outside a system of injustice and no one is a priori completely exempt from reproducing patterns of silencing. Not even ourselves, living and working in the “Global Southern” places of the world. Many political philosophers working and living in Latin America don’t even bother to read and cite their own colleagues. This is, to be sure, a shame, but there is a rationale behind this self-destructive practice. Latin American scholars know that their papers have even lesser chances of being sent to a reviewing process (we are usually desk-rejected) if they cite “too many” pieces in Spanish and by authors working outside of the academic centre.
In many reviews I’ve received in my career, I have been told to cite books by people from the centre just because they are trending or are being cited in the most prestigious Anglophone journals, even if they would contribute nothing to my piece and research. I have frequently been told by reviewers to give more information about the “particular” social-historical context I am writing from because readers don’t know a lot about it. This is an almost verbatim phrase from a review I got recently. I wonder if readers of Anglophone prestigious, Q1 journals stop being professional researchers the instant they start reading about José Carlos Mariátegui or Argentina’s last right-wing dictatorship. Why can’t they just do the research by themselves, why should we have to waste characters and words to educate an overeducated public? This is as tiresome as it is offensive. When I cite the work of non-Anglophone authors from outside of the imperial centres (UK, USA, Italy, Germany, and France, no matter the language they use to write), reviewers almost always demand that I include a reference to some famous native Anglophone (or Italian / German / French, without considering gender or race; the power differential here is simple geographical procedence) author who said similar things but decades after the authors I am quoting. I’ve read all your authors. Why haven’t they read “mine”? And why do they feel they have to suggest something else instead of just learning about “our” authors? This is what I want to reply to the reviewers. Of course, I don’t. I dilligently put the references they demand. I shouldn’t have to, but if I don’t, I don’t get published. There’s the imperial trick again.
English is also always a problem, but not for everyone who is not Anglophone. In 2020 I was in London doing research at LSE. I attended a lecture by a European political theorist. They gave the talk in English. Although they work at a United Statian University, their English was poor. The room was packed. The lecture was mediocre. I was annoyed. “Why do they feel they don’t have to make an effort to pronounce in an intelligible way?”, I thought. When I speak they don’t listen to me like that, with concentrated attention and making an effort to understand me. The reason is in plain view: coloniality of power. If you come from powerful European countries, you don’t need to ask for permission. You don’t need to excel. You don’t need to have something absolutely original to say. You just show up and talk. If you are from, let’s say, Argentina, and you work there (here), you have to adapt to the traditional analytic way of writing and arguing so typical in Anglophone contexts, including citing their literature, if you want to enter the room in the first place. You are not even allowed to use neologisms, although the omnipresent use of English as a lingua franca should have already made this practice at least tolerated. One cannot expect everyone to speak English and English to remain “English” all the same. Inclusion changes the game, if it doesn’t, then it is not isegoria what is going on but cultural homogenisation. (Here is a proposal for inclusive practices regarding Enlgish as a lingua franca). The manifest “Rethinking English as a lingua franca in scientific-academic contexts” offers a detailed critique of the idea and imposition of English as a lingua franca. I endorse it 100 %. (Here in Spanish, open access; here in Portuguese).
In my particular case, I am frequently invited to the academic centre, sometimes to write book chapters, encyclopaedia entries, and papers for special issues, sometimes to give talks and lectures. Not once have I not thought it was not tokenism. Maybe it is my own inferiority complex distorting my perception of reality, but we know from Frantz Fanon which is the origin of this inferiorisation.
I used to be pretty annoyed by this whole situation until I realised that I don’t need to try to enter conversations where I am not going to be heard, understood, or taken seriously. The fact is that we don’t need to be recognised as philosophers by those who willingly ignore our political philosophy. And this is why it is hard for me to participate in forums such as this blog. I just don’t want to receive the same comments I get when I send a paper to an Anglophone, Q1 journal, to put it simply.
But I also want to keep trying, not to feel accepted and to belong, but because I do believe in transnational solidarity and the collective production of emancipatory knowledge. It is a matter of recognition, and a question of whether it is possible for the coloniser to recognise the colonised, to name Fanon once more.
UBI: Short-Term Results from a Long-Term Experiment in Kenya
Abstract: “What would be the consequences of a long-term commitment to provide everyone enough money to meet their basic needs? We examine this hotly debated issue in the context of a unique eld experiment in rural Kenya. Communities receiving UBI experienced substantial economic expansion|more enterprises, higher revenues, costs, and net revenues|and structural shifts, with the […]
The post UBI: Short-Term Results from a Long-Term Experiment in Kenya appeared first on BIEN — Basic Income Earth Network.
Q and A with David Stainforth on Predicting Our Climate Future: What We Know, What We Don’t Know, and What We Can’t Know
We speak to David Stainforth about his new book, Predicting Our Climate Future: What We Know, What We Don’t Know, and What We Can’t Know, which argues for a re-evaluation of how we go about the study of climate change in the physical sciences, the social sciences, economics and policy.
You can watch a public LSE event with David Stainforth to launch the book from October 2023 on YouTube here.
Predicting Our Climate Future: What We Know, What We Don’t Know, and What We Can’t Know. David Stainforth. Oxford University Press. 2023.
Find this book: 
Q: Where did the idea for the book come from and what were you setting out to do in writing it?
Between 2000 and 2015, I became aware that my perspective on what we should be trying to do in climate change science wasn’t at all reflected in the practice of research in research institutions. It seemed to me important to write something that would engage people with all the fascinating challenges that exist in understanding the problems of climate change. Doing so, I hoped, would help make clear the separation between what we know and what we don’t know.
Many big, fundamental, questions – philosophical, mathematical, physical, and economic questions – about climate change tend not to be examined, probably because of the urgency for society to act.
If I was a sixth-former now, I would certainly see climate change as an important issue for society, but I’m not sure I would be passionate about trying to understand it. That’s because it appears that we already understand it, although in fact we don’t. Many big, fundamental, questions – philosophical, mathematical, physical, and economic questions – about climate change tend not to be examined, probably because of the urgency for society to act. My book addresses these questions. I would love for my book to stimulate high-school students and undergraduates across diverse disciplines to say, actually, there’s something really fascinating to get my teeth into here; something that humanity hasn’t yet understood.
Of course, none of this undermines the importance and urgency of acting on climate change, but acting and understanding need to go hand in hand.
Q: What are the limitations of scientists’ understanding of the climate system? How do these affect our ability to predict how the climate will change?
The central issue is complexity and there are two aspects of complexity that create a barrier to predicting what the climate future will look like.
The climate system is made up of many components – the atmosphere, the oceans, land ecosystems, ocean ecosystems, biogeochemical systems, the cryosphere etc. Many of these can be broken down further into subsystems, and all of this is before you get into the social aspects. The first aspect of complexity is simply how these many disparate components interact.
Certain types of system, like the climate system, have real barriers to predictability because what happens in the future can be very sensitive to the state of the system today. This is what’s meant by the “butterfly effect”.
The second aspect of complexity is more mathematical. Certain types of system, like the climate system, have real barriers to predictability because what happens in the future can be very sensitive to the state of the system today. This is what’s meant by the “butterfly effect”. At the same time, the relationship between our models and reality is unclear: how close does a model have to be to reality for it to be able to tell us something about how reality will behave? That’s a difficult question to answer; it might be that our models could represent reality very closely, but still provide unreliable predictions. This is something that Erica Thompson has named the “hawkmoth effect”; it’s something we haven’t really begun to study.
These types of complexity affect how we should be designing our climate models and what sort of experiments we should run with them.
Q: What do Global Climate Models (GCMs) do and what are their limitations?
Global Climate Models break down the atmosphere and ocean into grid points and at each grid point they solve the equations of motion to tell us how things change over time. This is what’s known as a reductionist approach to modelling, and it allows us to work out what the state of the atmosphere or ocean system might be at some point in the future. Solving the equations on a computer can typically only tell us how things will change over about 10 minutes, so you’ve got to repeat the process millions of times to get information for 100 years ahead.
There are lots of elements of the climate system that can’t be modelled [in a reductionist] way, either because we don’t know what the fundamental equations are or because the processes take place on scales that are far too small to include in the models.
But there are lots of elements of the climate system that can’t be modelled that way, either because we don’t know what the fundamental equations are or because the processes take place on scales that are far too small to include in the models. Examples include how ecosystems absorb and release carbon dioxide and how clouds and rainfall form. For these components there are various different ways to approximate the processes at play, but it’s not easy to know how reliable these approximations are. And because all aspects of the climate system affect all the other aspects of the climate system, this means that the model predictions can’t simply be taken as predictions of reality.
Q: Why do we rely so heavily on GCMs for climate prediction and policy development today? Is there a danger in relying too heavily on these models?
When we study climate change, we don’t have multiple climates to examine. The time scales and the system are defined: it’s our real-world climate system that we’re interested in, and how it will change through the 21st century. We are doing an experiment on the real climate system through humanity’s emissions of greenhouse gases, but we’ll only ever get one result, and that will come too late to be of much use to us. The models enable us to study what we can’t study in reality – for instance, multiple possible scenarios of future greenhouse gas emissions. But we need to always remember that we’re studying a model, not reality. The power, the detail and the ubiquity of the models encourages us to avoid asking the big questions about how the model predictions relate to reality – whether what they’re telling us is actually what we think will happen.
When we study climate change, we don’t have multiple climates to examine. The time scales and the system are defined: it’s our real-world climate system that we’re interested in, and how it will change through the 21st century.
Research on climate, particularly with models, has grown out of work on weather forecasting. The reliability of weather forecasts over the last 20 to 30 years has massively improved, principally because of these models. But in the shift from weather forecasting to climate forecasting, we are dealing with a fundamentally different problem. In weather forecasting, we don’t need to get the whole of the climate system right: it’s mainly just about simulating the atmosphere. Furthermore, we repeat the weather forecasting process three or four times a day, so we can compare the model’s predictions against what happens in reality. That means we can test whether our models are doing a good job in a way that is impossible for climate predictions
With climate, you need to bring in many other elements of the climate system, including oceans and ecosystems, and we don’t have the same possibility to verify the results. This puts us in a very different domain, but the problem is that it doesn’t feel that way. It feels as though weather forecasting and climate predictions are very similar because they use similar, related models. This represents a barrier to using the models effectively to help us provide reliable information about future climate.
Q: Why do you argue that greater diversity of climate models rather than greater “realism” of climate models should be the goal for better climate prediction?
Aiming for realism tends to take us to higher and higher resolution models. These models represent atmospheric behaviour better and they look more realistic, but this lulls us into a false sense of security. Despite the “realistic” appearance of these models, we can’t tell if they are accurate because we’ve never observed the planet in the warmed state that we’re interested in.
High-resolution models also take a lot of computing time to run, and consequently they remove the possibility of exploring other uncertainties such as how we represent the carbon cycle or biogeochemical processes. There’s a substantial risk therefore that we adapt society to be resilient to the changes in our models, when what might actually happen could be very different.
If […] we were to address different ways of building our models and of accounting for the many uncertainties, this would give us a diversity of predictions.
If instead we were to address different ways of building our models and of accounting for the many uncertainties, this would give us a diversity of predictions. Having a better understanding of the wide range of different changes that could plausibly happen would enable us to be better prepared and is, in my view, crucial to building a robust response to climate change.
Q: How does the separation between disciplines, which approach the issue in very different ways, hamper our understanding of, and ability to act on, climate change?
Assessments of the economics of climate change and of the consequences for our societies, for our wealth, for our welfare etc., often don’t take sufficient account of the uncertainties in the physical science. There is a real need for economists to understand the processes of the physical sciences better.
Assessments of the economics of climate change and of the consequences for our societies, for our wealth, for our welfare etc., often don’t take sufficient account of the uncertainties in the physical science
However, if we want the physical climate sciences to help us prepare effectively for our future world, then we need to ask, what are the questions that are being addressed by agricultural scientists, by city planners, by economists and by policy makers. Only when we are clear what kind of information is being sought, can we direct the physical sciences in a useful way. At the moment, the physical scientists set the questions and pass on the resulting information to social scientists rather than focusing their experiments and models on what social scientists and society need to know most.
We are stuck in a traditional approach which is not serving society well.
Q: How could we enable greater interdisciplinary research around climate change?
We require big changes in how we do climate change research. We need to be a lot clearer about what we’re trying to address and how the connections between disciplines work. I think that means high-level change to how we study the problem.
Historically climate change research has been very siloed, as academia generally is. There is a need for the research funders to grasp the nettle of wholesale change and for universities and research institutes to come together and create career paths that enable people to research across disciplinary boundaries.
There is a need for the research funders to grasp the nettle of wholesale change and for universities and research institutes to come together and create career paths that enable people to research across disciplinary boundaries.
I don’t think the importance of multidisciplinarity for understanding fundamental features of the threats posed by climate change has been fully recognised. There are still many funding calls that are essentially answer-driven. It’s a “tell us what will happen to this bit of the system” approach, but that’s not what climate change is. You can’t tell what’s going to happen to one aspect without connecting it with everything else. It’s a big, complex problem and needs to be addressed as such.
As a starting point we need funding – 10, 20 million pounds – for a centre that can bring truly diverse researchers together from philosophy to physics to economics, and give them the stability of five to 10 years to work on these problems together. That’s the starting place for better information about our climate future. It’s also the starting place for training a cohort of experts who have both the breadth and depth of knowledge to be able to build climate resilient societies and communicate what climate change risks actually look like.
Note: This interview gives the views of the author, and not the position of the LSE Review of Books blog, or of the London School of Economics and Political Science. The interview was conducted by Anna D’Alton, Managing Editor of LSE Review of Books.
Main Image: Arctic sea ice by Kathryn Hansen / NASA on Flickr.
A Night at the Newseum
Unfortunately, for all their skills as observers of the world, journalists are notoriously unable or unwilling to see how the business that subsidised their story-telling actually worked and the economic forces that destroyed them
Statement launch and online Parliamentary lobby, Tuesday 21 July
Online meeting: Tuesday 21 July, 5.30-7.00pm
Covid-19 has plunged UK higher education into a deep financial crisis. Tens of thousands of posts are at risk, and over a dozen universities are predicted to be at risk of outright bankruptcy. But the pandemic has exposed problems, rather than creating them. Well before Covid-19, marketisation was wreaking havoc on higher education.
So far, the government has offered only limited support, amounting to little more than a sticking plaster on a fundamentally flawed system.
Through two large online meetings, the Convention for Higher Education has developed a set of demands for policymakers on how to rescue universities and put our higher education system onto a truly sustainable footing.
Now is the time to start pressing our politicians for meaningful action. This starts with an online lobby with the Shadow Higher Education Minister, Emma Hardy MP.
This is a crucial opportunity to take real action to defend our universities and students. Please join us!
Schedule:
- Prof John Holmwood (Campaign for the Public University) will introduce the Convention for Higher Education’s recommendations for a policy response.
- Representatives from the hardest-hit institutions (including Reading, Liverpool, SOAS) will share what is happening to them.
- Emma Hardy MP, Labour shadow Higher Education minister, will outline the risks to universities and what Labour believes the government should do to provide support.
- Lord Rowan Williams (Council for the Defence of British Universities) and Matt Crilly (NUS Scotland President) will offer short responses.
Other speakers have been invited to discuss how we can build the movement to defend higher education and access. We will also take as many questions from the floor as possible.
The meeting was recorded.
Smart People Work Everywhere - using your research skills outside academia
A panel discuss using your research degree outside academia. Research degrees - what are they good for? Can you use the skills you have acquired during your DPhil in a career outside academia - and why would you want to? Professor Philip Bullock, Director of TORCH, chairs this panel discussion with individuals from a diverse range of employment sectors who use the skills they acquired during their research degrees in their current roles. Hear about their career paths to date, learn more about their current roles, and find out how they utilise their research skills in their professional lives. The panellists are Professor Kate Williams (author, historian, TV presenter and Professor of History at the University of Reading), Dr Mark Byford (partner at Egon Zehnder) and Dr Michael Pye (Investment Manager at Baillie Gifford).
The ABC of Trust
With Australians trusting media platforms less than do people in just about every other country, why would you set about dismantling the one institution they trust the most? The Australian Broadcasting Corporation, our 86-year-old taxpayer-funded and constantly beleaguered public broadcaster, regularly tops surveys as one of the country’s few remaining […]
‘ “Hitler had a valid argument against some Jews”: Repertoires for the denial of antisemitism in Facebook discussion of a survey of attitudes to Jews and Israel’ (now in print)
My article ‘ “Hitler had a valid argument against some Jews”: repertoires for the denial of antisemitism in Facebook discussion of a survey of attitudes to Jews and Israel’, which was published online in April this year, has now appeared in the August issue of Discourse, Context & Media. It explains the background to the antisemitism crisis that has now engulfed the Labour Party leadership, then analyses some of the ways in which Labour supporters deny the existence of antisemitism before looking at how the largest unofficial Labour Party Facebook group makes the problem worse by readily expelling those who challenge antisemitism but only expelling antisemites for extreme transgressions.
The version of the article that was printed is now the version of record and can also be read online (where it replaces the earlier ‘online first’ version). If you do not have a subscription to Discourse, Context & Media, you can read the accepted manuscript draft on this website or contact me to request a legal copy of the version of record.
Bibliographic details
Allington, D. (2018) ‘ “Hitler had a valid argument against some Jews”: Repertoires for the denial of antisemitism in Facebook discussion of a survey of attitudes to Jews and Israel’. Discourse, Context, and Media 24: 129-136.
Keywords
Anti-Semitism; Anti-Zionism; Denial of racism; Attitudes; Zionism; Israel; Jews; Labour Party; Facebook; Social media
Highlights
- Antisemitism may be simultaneously expressed and denied
- Antisemitism is often expressed in statements about a Jewish or ‘Zionist’ elite
- Research and policy should recognise the ways in which antisemitism is expressed
- Left wing Facebook groups do not effectively police the expression of antisemitism
- Group members who challenge antisemitism may face exclusion
Abstract
Existing research suggests that, in contemporary liberal democracies, complaints of racism are routinely rejected and prejudice may be both expressed and disavowed in the same breath. Surveys and historical research have established that – both in democratic states and in those of the Soviet Bloc (while it existed) – antisemitism has long been related to or expressed in the form of statements about Israel or ‘Zionist’, permitting anti-Jewish attitudes to circulate under cover of political critique. This article looks at how the findings of a survey of anti-Jewish and anti-Israeli attitudes were rejected by users of three Facebook pages associated with the British Left. Through thematic discourse analysis, three recurrent repertoires are identified: firstly, what David Hirsh calls the ‘Livingstone Formulation’ (i.e. the argument that complaints of antisemitism are made in bad faith to protect Israel and/or attack the Left), secondly, accusations of flawed methodology similar to those with which UK Labour Party supporters routinely dismiss the findings of unfavourable opinion polls, and thirdly, the argument that, because certain classically antisemitic beliefs pertain to a supposed Jewish or ‘Zionist’ elite and not to Jews in general, they are not antisemitic. In one case, the latter repertoire facilitates virtually unopposed apologism for Adolf Hitler. Contextual evidence suggests that the dominance of such repertoires within one very large UK Labour Party-aligned group may be the result of action on the part of certain ‘admins’ or moderators. It is argued that awareness of the repertoires used to express and defend antisemitic attitudes should inform the design of quantitative research into the latter, and be taken account of in the formulation of policy measures aiming to restrict or counter hate speech (in social media and elsewhere).
Voters in the 2017 general election – and how they voted previously
This is the third and final part of my preliminary analysis of groups of voters defined by the choices they made in the 2015 general election, the 2016 European Union membership referendum, and the 2017 general election (c.f. Stephen Bush’s nine voter groups), using an English subset of responses to the British Election Study’s post-election face-to-face survey. In the first part, I looked at the ten largest groups, from Conservative-Leave-Conservative to Conservative-Remain-Labour, both in terms of their size and in terms of their self-declared likelihood to vote for various parties in future, and found that Labour Remainers were not only more numerous but (on their own assessment) more likely to be poached than Labour Leavers, while the smaller group of Conservative Remainers who had switched to voting Labour were quite likely to switch again. In the second part, I looked at six groups of voters who had in common that they could have voted but did not in the 2015 general election, finding that most of them did not vote either in the 2016 referendum or the 2017 general election, and that only the minority who voted Remain in the 2016 referendum were more likely than not to have voted in the 2017 general election.
To finish up for now, here’s a single chart showing all voter groups which participated in the 2017 general election (weighted by demographic group and by 2017 vote). Each quarter of the chart below shows the members of the sample who voted for one of the four main parties. These voters are further subdivided into columns to show how they voted in the referendum and into coloured blocks to show who they voted for in 2015 (note that black covers both non-voting and voting outside the four main parties, which most often meant voting Green as the data are from England only):
What does this chart tell us? It tells us that, at least within this random sample of 1874 voters (1777 after weighting)…
- Most of those who voted for the two right-wing parties in 2017 had voted Leave in 2016, while most of those who voted for the two liberal-left wing parties in 2017 had voted Remain – and this is true whether we focus on voters retained or on new voters gained
- However, the Remainer proportion of the 2017 Conservative vote is substantially greater than the Leaver proportion of the 2017 Labour vote
- The Conservative Party picked up most of the (Leave-voting) UKIP vote from 2015
- But it picked up more votes from Labour Remainers than it did from Labour Leavers
- And so (less surprisingly) did the Liberal Democrats
- In fact, the Labour Party and the Liberal Democrats both picked up far more votes from Remainers than from Leavers – both from the Conservatives and from each other
- Those 2017 voters who did not vote in the 2016 referendum mostly ended up voting Labour
- Every party except UKIP both gained and lost a substantial proportion of voters between 2015 and 2017
- UKIP definitely lost voters, but you have to zoom into the chart to see its minuscule gains
To summarise: on the evidence of these data, the only really notable movement among Leavers seems to have been the metamorphosis of most 2015 UKIP voters into 2017 Conservative voters. Those voters are unlikely to go back to UKIP because, on the brink of financial ruin and with no credible leadership, UKIP is in no position to win them back. Otherwise, the movement that has taken place appears to have been largely among Remain voters: more Remainers than Leavers would seem to have gone in both directions between Labour and the Conservatives and between Labour and the Liberal Democrats, while the Liberal Democrats picked up a not inconsiderable number of formerly Conservative Remainers and while a larger block of Remain voters who had not voted for any of the four main parties in 2015 simultaneously fell into orbit around Labour.
The Labour and Conservative Parties did nothing to court the Remain vote last year, and have done nothing to court it since. But it looks like it’s the Remain vote that is volatile now.
Ten voter groups: combinations of EU referendum and general election votes in the BES 2017 face-to-face survey
Like many, I read with interest Stephen Bush’s recent article on ‘The nine voter groups who are more important than Labour Leavers’. If Bush were a grant awarding institution, there would be money available for researching those groups. Well, he isn’t, so there isn’t, but I like a challenge so I’m going to make a start anyway – using open data from the British Election Study (henceforth, BES). To be more specific, I’ll be using the BES 2017 face-to-face survey, which was conducted after the election and uses what should probably be considered a more genuinely random sample than the online waves.
If we focus only on England (because the other parts of the UK have really quite different political systems), this gives us 1874 respondents, or 1839 after weighting for demographic group. Even after weighting, Labour voters are over-represented, but we’re not trying to predict last year’s election – we’re trying to understand why people made the voting choices that they did, and to use that information to derive hints about what voting choices they might make in future.
Bush’s general approach was to identify groups by how they have voted in recent years. Groups identified in this way are more or less important, if I understand him correctly, according to how much they might sway the result of future elections. And a group’s ability to do that would presumably depend upon (a) its size and (b) its likelihood of flipping from one party to another, given some sort of predictable event such as a political party coming out for some particular policy.
What sort of a policy might that be? Respondents to the survey gave a pretty clear hint of that in their responses to the open question, ‘As far as you’re concerned, what is the single most important issue facing the country at the present time?’ Although Jeremy Corbyn and Theresa May largely succeeded in avoiding discussing Brexit policy during the 2017 election campaign, Brexit was clearly the most popular answer. And well it might have been, I might add, because all the other issues in the top five clearly depend on what kind of a Brexit the UK actually gets. (Note for the nerds: what I’m actually counting here is the number of respondents who gave each of these words as a one-word answer, plus the number of respondents who began their answers with one of these words, or a morphologically related word, e.g. ‘immigrants’ was counted under ‘immigration’. Also, throughout this article I’m using the BES team’s wt_demog weighting.)
The overwhelming importance given to Brexit is analytically convenient, because one of the last three important UK-wide votes was the 2016 referendum on continued membership of the EU, so if we use that referendum to define our groups (as Bush did in some cases), then the definition of the groups themselves will give us an indication of how they might feel about the policy area that their members seem to regard as most important.
So now to those groups.
There are some that I’d like to come to at a later date (in particular, ‘Conservative voters in 2017’ and ‘Labour 2017, Gives An Answer Other Than “Jeremy Corbyn” When Asked Who Would Make The Best Prime Minister’). But right now I’m intrigued by the possibility Bush raises of dividing up the electorate by combinations of 2015 General Election, 2016 EU referendum, and 2017 General Election votes
Bush lists four of these: ‘Conservative 2015, Remain 2016, Labour 2017’, ‘Conservative 2015, Remain 2016, Conservatives 2017’, ‘Non-voting until 2016, Remain 2016, Labour 2017’, and ‘Non-voting until 2016, Leave 2016, Non-voting 2017’ (the latter of which he lumped together with an implied fifth group, ‘UKIP 2015, Leave 2016, Non-voting 2017’). But even if we limit ourselves to the four main parties (Conservative, Labour, Liberal Democrat, and UKIP) plus ‘other’ as a catch-all plus non-voting in the two general elections, plus the three possible responses to the 2016 referendum (Leave, Remain, and non-voting), there are an awful lot of potential groups: 108 of them, to be precise. Or 126 if we distinguish those who didn’t vote in 2015 from those who couldn’t vote, e.g. because they were too young. (I made this distinction in my analysis but it didn’t seem to make any difference to the overall picture.) Most of these groups are going to be too small as to be important. If voters are evenly distributed between all 108 or 126 groups, then less than 1% will fall into each, and if they are not, then less than 1% will fall into each of most of them.
With R’s dplyr package, it’s quite easy to divide up survey respondents according to combinations of votes (using group_by), and then calculate each group’s average responses to the question ‘How likely is it that you would ever vote for each of the following parties?’ (on a scale from 0 to 10) to give a sense of their probability of flipping in the next election (using summarise). Here are the ten largest:
As the table shows, the largest groups are of people whose voting behaviour was the same in 2017 and 2015, regardless of what they did or didn’t do in 2016. That’s not particularly surprising, because the British electorate isn’t known for shopping around: by and large, Conservative voters vote Conservative, Labour voters vote Labour, and non-voters don’t vote.
But the table contains a very clear hint that Bush might be right in his main thesis that ‘Labour Leavers – that is, voters who backed Labour in 2015 and Leave in the referendum of 2016 – have received an outsized share of attention and analysis’. As we see from the above, the ‘Labour 2015, Remain 2016, Labour 2017’ group is much, much bigger than the ‘Labour 2015, Leave 2016, Labour 2017’ group, and – given the probability scores – the former looks much more amenable to being poached by the (anti-Brexit) Liberal Democrats than the latter does by the (pro-Brexit) UKIP and Conservative Party. Meanwhile, there was no other combination beginning ‘Labour 2015, Leave 2016’ that was large enough to make the top 10, indicating that there has been no major exodus of Leave voters from Labour to elsewhere.
When we remember the recent survey finding that ‘fewer than one third (32%) [of Labour Leavers] think [that leaving the EU is] very important’ while ‘over half (51%) [of Labour Remainers] say [that staying in the EU] is very important’, there is therefore clearly now a substantial body of evidence to indicate the greater potential for Labour Remainers than Labour Leavers to influence the result of a future general election – provided that somebody makes a bid for their support. Whoever it is, it probably won’t be the Labour leader, a lifelong Eurosceptic who called for the invocation of Article 50 before even Nigel Farage. But as I said last June, Paris might be worth a mass.
Looking further down the list, ‘Conservative 2015, Remain 2016, Labour 2017’ looks very much like a floating vote, giving very similar probability scores for all parties except UKIP, which it would seem to regard as beyond the pale. In fact, the only top 10 group giving UKIP a score higher than 3.1 was ‘UKIP 2015, Leave 2016, Conservative 2017’: the Leave-voting UKIP-Conservative switchers who decimated Paul Nuttall’s already shaky credibility last June. Those switchers might switch again. But, based on the probability scores, they don’t seem to like Labour or the Liberal Democrats very much, and right now the chances of UKIP’s winning back anybody’s vote with its current leadership and financial difficulties are looking pretty remote. And even the 3.1 came from ‘None 2015, Leave 2016, None 2017’: a small group that is, like the much larger ‘None 2015, None 2016, None 2017’, unlikely to vote for anyone in the near future (not only on the evidence of its avowedly low likelihood of voting for any of the four main parties but on the evidence of, ahem, past behaviour). Those two groups can, I think, fairly safely be written off as unimportant, at least in the sense defined above. (I know that sounds elitist, but if people don’t want to vote for anything that’s available, then they can’t influence elections.) The Conservatives might be able to attract the ‘UKIP 2015, Leave 2016, UKIP 2017’ group next time around, but it was too small to make the top ten above and therefore its departure from the UKIP fold probably won’t have much of an impact on anything now that the bulk of 2015 UKIP voters has already left for pastures new.
So it looks as if UKIP voters have had their (admittedly gigantic) effect and are now a spent force, and – all in all – the groups to watch from now on are the very large group of Labour Remainers – only a small proportion of which would need to peel off and vote for another party to make an impact at the polls – and the much smaller group of Remain-voting Conservative-Labour switchers, whose votes have migrated once and (even if we did not have the evidence of the probability scores above) might therefore be assumed to be more than averagely predisposed to migrate again. Labour Leavers are much smaller in number than one of the aforementioned, and – it seems – more likely than both to stay put.
Now to the inevitable caveat. While the approximate relative sizes of these groups are probably a robust finding (because the poll itself was so large), the average probability scores for a group become less and less reliable as the size of the group falls: for example, the averages in the final row in the table above are the findings of what was in effect a poll of 29 people, so the margin of error will be huge, and I mention the scores above only because they are more-or-less what we might expect given that particular group’s voting history.
We could find greater numbers of people falling within each group from the BES online panel, but that has representativeness problems of its own, and what we’re coming to here is an essential problem of the approach of splitting survey respondents up into discrete groups of successively smaller size. I’ve done some more analysis that takes a slightly different approach in order to mitigate that problem, but I’ll save it for a future post.