Methods and epistemic fracture: reviving the information moral economy

The value of social research methods is that it produces independent evidence on the nature of society, social-economic problems and challenges, and potentially agreed ways of reaching effective solutions. There are two challenges to social research methods: one is the epistemic fracture of societies, where awkward evidence is mistrusted or denied. The other is the technocratic assumption that all will be resolved by data, and that theory-less, structure-less, data will answer all questions. These are challenges are all the more serious because they have something to them. Social research, like any other institutional practice, can be governed by agendas that are hidden or unquestioned, or partial. Much effective research takes place outside of institutions, and platform data provides more data than we can seriously use without developing our computational skills and tools. 

We have to get these challenges in context first of all. Despite the image of an atomised, divided country living solely on the warmth of social media rage, people in Britain are fairly trusting. They just do not trust central government that much. There is epistemic fracture though. Trust in established new sources is not strong across the board and has exhibited a growing vertical and horizontal epistemic fracture.  There are many features to this epistemic fracture, showing the evolution of public debate and the social sorting of society into a self referential, credentialed class and the rest.

One that has gathered a lot of interest has been the operation of malicious disinformation operations. Thomas Rid (2020) has written an accessible history and theoretical study of information operations. As he shows overall disinformation operations are about the intent, rather than the form, of the operation. For that reason tactical moves like disclosing a campaign’s existence can be effective if the aim is to generate uncertainty. According to Rid (2020) what they do is attack the liberal epistemic order. This order has some features: that facts have their own life, independent of values and interests: that expertise should be independent of immediate political and strategic interest.

That institutions should be built around those principles – a relatively impartial media, quiescent trade unions, universities, even churches and other private institutions, are part of the epistemic matrix undergirding liberalism. It doesn’t take a genius to work out that this order has been eroded from multiple angles over the past decades by processes that have nothing to do with information operations. Independent media institutions like established newspapers have become uneconomic and replaced with a click-driven, rage fuelled, tribalist media. Increasingly the old institutions mimic the new. The independence universities and the professions has been similarly eroded by the imposition of market driven governance on higher education, the NHS, and other bodies. This isn’t a call to all just get along because that is part of the problem: we are not grasping the power of vertical integration of self, context and information spheres. Disinformation can be a red herring and an excuse for the failure of institutions to operate in the public interest, and to understand why this is the case. 

The horizontal aspect of this is that people with high social and economic capital have more trust in institutions. The vertical aspect is that in some societies trust is politically divided and people only trust news sources that represent their ‘side’. These two dimensions overlay each other. We should not be too surprised. People whose lives were easily adapted to COVID lockdown because they had secure housing, could work from home easily, and did not have their children’s education much disrupted are more trusting of institutions and establishment media sources. This aspect of epistemic fracture was hidden from sight, and instead mistrust in COVID messaging was often attributed to disinformation and malicious actors. There are plenty of disinformation operations but their effectiveness is questionable. Social research should provide a framework to move beyond panicked responses that seek to close down the public sphere. 

Historical research and media analysis also helps us put these problems in context. It also does not take a genius to note that the liberal epistemic order was always less than it was cracked up to be, as studied in the work of the Glasgow University Media Group among others. If we look at the history of trade union politics in France and Italy to take two cases we see a fractured information order without a public square consensus.

We can use critical digital analysis to point to some specific developments more recently: the financialisation and datafication of disinformation markets, and the vertical integration of political power with distributed media which makes use of of a distributed labour infrastructure which is agile and available. It is noticeable that they use some of the same infrastructure of doubt and uncertainty which is employed by spam and ransomware operations.  They deploy sophisticated, data informed semiotic tools. The recent history of disinformation strikes at a number of question at the intersection of information science, sociology of markets, sociology of technology and the philosophy of knowledge: how can disinformation be defined, recognised and how can systems be made resilient against it. There are several thorny ontological and epistemological questions e.g. between the politics of knowledge, preference falsification, technical and social verification. 

One way of doing that is to reframe the issue in a way supported by social research methods. It cannot be about pure information (no such thing) or uncontested knowledge (undesirable) but creating local, critical spaces where communities can decide on the informational priorities that matter to them. Returning to my starting point, we need to understand an epistemic contradiction: the most liberal viewpoints demand the most closure when they attempt to grasp the motives of others. People who voted for Britain leaving the EU have a much more accurate understanding of the Remain side’s motives than Remainers do of theirs. They are epistemically privileged, if socially marginalised. My hypothesis is that epistemic gap is due to the Remain side having a much more socially integrated multi layered knowledge structure which operates through everyday spaces (work, university, neighbourhood) in ways that the Leave side does not. The reason the EU vote was a surprise to many was that this conceptual integration around Leave is more fragmented, less socially/culturally powerful, but is still there.

What we should establish is the role of social research in the creation of an information moral economy. People who answer surveys, fill in census forms, and put up with us when we interview them or hang out in their spaces, are participating in a moral economic that recognises some civic commonality and public good coming from research. The moral economy is instrumental and emotionally bound, and recognising it means we need to understand our duties towards norms of reciprocity and the public good, the role our work has in vital questions of the distribution of economic and social resources.

Rid T (2020) Active Measures: The Secret History of Disinformation and Political Warfare. Farrar, Straus and Giroux.

Society gets the crime it designs

Crime is designed in. Organised crime is intertwined in society and its institutions, its character reflects them, and it uses society’s technical affordances. Digital capitalism provides tools to increase the reach and impact of criminal activity Risks are distributed along with social vulnerabilities. Some crime is required and necessary because many people cannot turn to the state for help. If the only source of order is the local gangster, the only source of liquid capital the local loan shark/drug lord, the only way to secure status or survival is through gang membership, if social cohesion relies on gang influence, if social order relies on the underworld,  if an economy relies on a supply of illicit labour, if it depends on minerals produced in defiance of environmental regulations, if the most productive and highly capitalised sector of the economy ignores regulatory compliance; if survival depends on it, we can talk of crime as necessary. As an example, the Yakuza have at times been the most flexible and adaptable sector of the Japanese economy.

Technical and social networks are crucial to the development of criminal capacity to organise effectively. Mafia organisations benefit from ‘rents’ (ie charging to non interfere with everyday business) and ‘protection’ (obtaining control over resources, labour and skills, rather than producing those things). Most capitalist activity comes from that. Social media obtains extractive control over personal data. Amazon uses economic privileges awarded by the courts to charge a rent from sellers and book publishers. These aren’t even the nastiest examples.

The capacity to create hybrid systems in terms of state-crime relations, legal-illegal and organisational-platform/infrastructure is central. The infrastructure allows participants to manage and broker risk. On a national and global level state formation and deformation leads to the creation of conflict zones and black spots. At one time criminologists hypothesised that people became labelled as deviant and adopted a deviant identity. Crime existed in the left over grey spaces of the licit world, the abode of the righteous dopefiend. Now, we see crime designed into systems, and crime that creates its own context, its own technology and architecture. As an example, telemarketing fraud practitioners who have entirely no sympathy at all for their victims (Shover, Coffey and Hobbs, 2003). They view themselves as entrepreneurs taking money from the foolish who are complicit in their own victimisation.

There was a parallel between the tele-fraudsters’ own lifestyles and the way they characterise their victims. They saw their victims as reckless gamblers eager to give their own money away. The fraudsters’ own lifestyles often involved high stakes gambling and plenty of splashing the cash, so they seemed to think that their victims wanted to be like them but couldn’t. Those running the tele business engaged in the usual distancing involved in white-collar crime. Those who ran the business blamed their salesmen for going too far. Salesmen blamed their bosses for giving them incentives to illegal behaviour.  The fraudsters thought they merited a lavish lifestyle but were unable to obtain it by mainstream means. Telefraud offered them large amounts of ready cash for little expenditure of effort. There is nothing these convicted criminals say or do that wouldn’t fit very well with a company operating legally but at the margins of personal morality. They rely on the same systems, the same data, the same language.

Ruggiero V (2013) The Crimes of the Economy: A Criminological Analysis of Economic Thought. London: Routledge. DOI: 10.4324/9780203385500.
Shover N, Coffey GS and Hobbs D (2003) Crime on the Line. Telemarketing and the Changing Nature of Professional Crime. The British Journal of Criminology 43: 489.

Writing the further work bit

You know that bit at the end of your dissertation or research paper where you suggest what could be done next, and which is always the last thing everyone writes and which you give less thought to than a status update on Insta? You are doing it wrong. Typically these sections are either written in Fantasy Project style, imagining some other study that is not going to happen, or Fill in the Blanks, suggesting some tweaks to sampling or doing more of what you had done. Stop doing that. Nobody cares. Do not waste space imagining some new project. You will never do it. Stop pretending you will ever go back and fix the project that is now in the rear view mirror.

Instead, make some plans that are achievable. Identify other datasets that yours can be linked to. This gives you opportunities for further writing, looking at how your data correlates to another context. The aim is to show how your findings could work with others and how they feed into a macro context which meshes with data, theory and findings from other projects. Ask how your data works with other data types. How would your hypothesis play out in other contexts. How consistent would it be in other cases. How should it be tested against new data.

As an example, we have sorted cybercrime groupings on two dimensions, closed/open in terms of how porous their external boundaries are, and status driven/pecuniary in terms of their motive and business model. A Russian cybercrime grouping is closed and pecuniary within limits. It acts in the interests of the Russian state at times, seeking political legitimacy and in group status. Where might cybercrime groups yet to be brought into being sit and why? Would identity or language based groupings cluster at one end or another? Could it be applied to cases in the UNODC Sherloc database? What new hypotheses could be generated? What might we expect of Islamist or right wing terrorism, or the relationship between cyberwar and state conflict? One advantage is that you can take risks within the bounds of plausibility. The further work should be a genuine map ahead for you which takes you to new places, so think in terms of the possibilities it offers for new thinking and collaboration.