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‘Is there a right not to be researched? Is there a right to do research? Informed consent and the principle of autonomy

By Martyn Hammersley & Anna Traianou

The right not to supply data about oneself is built into the principle of informed consent. But is there also a right to control the use of these data? Also, is there a right not to be researched, and does this too follow from the concept of informed consent? Finally, what about a right to research; and if there is such a right, who has this? As these questions indicate, a range of rights have been claimed in relation to social research, but the assumptions underpinning them have rarely been addressed. Yet it should be clear that these rights can come into conflict, so that we need to be clear about what would and would not be legitimate grounds for claiming them. This also requires giving attention to the very concept of right, and what different sorts of right there can be. These are the questions that we explore in our article.

They follow on from the issues that we addressed in our 2012 book Ethics in Qualitative Research (London, Sage), where we examined what count as ethical issues, and the meaning of the various principles that are central to research ethics: concerned with minimising harm, respecting autonomy, and preserving privacy. In working on that book we came to recognise some of the complexities involved in the notion of informed consent – regarding what counts as being informed, what counts as consenting, and what people are consenting to. Since it is widely assumed that there is a right to be informed that research is taking place, and a right to decide whether or not to supply or provide access to data, this led us on to thinking about the nature of the various rights surrounding social research.

However, the immediate prompt for the paper was a proposed conference in Canada that, unfortunately, did not take place because funding was not available – this was a follow-up to the ‘Ethics Rupture’ summit that had been held in 2012, organised by Will van den Hoonaard. We had been invited to contribute, and one of the issues that was to be the central at the conference was the rights of indigenous communities as regards participation in social research. We decided that this would provide an opportunity to explore the general issue of research rights. Around the same time, we had also been thinking about the nature of academic freedom, which also involves rights claims (Traianou, The erosion of academic freedom in UK Higher Education. Ethics in Science and Environmental Politics, 15(1), 2015, pp. 39-47; Hammersley, ‘Can academic freedom be justified? Reflections on the arguments of Robert Post and Stanley Fish’, Higher Education Quarterly, 70, 2, pp108-26, 2016). This, too, fed into our article. We explore some of the issues surrounding research rights, rather than providing definitive answers. It is our view that ethical judgments, along with those relating to methodology, must take account of the particular circumstances faced: blanket injunctions are not helpful. Different principles, and rights associated with them, need to be considered and reconciled, as far as possible, according to the particular character of the research and the situation in which it is being carried out. At the same time, it is essential that there is clear understanding of those principles and rights claims, and our aim was to highlight the need for this and to contribute to achieving it.

See full IJSRM article here.

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Conducting focus groups in a global pandemic

by Cordula Hinkes

The COVID-19 pandemic poses new challenges for researchers in the social sciences. Several research methods require communication and interaction between the researcher and respondents. Some of my colleagues were planning to conduct focus groups with consumers in multiple countries earlier this year. Due to travel restrictions and social distancing requirements, they had to put their plans on hold. Waiting for the restrictions to be lifted, they re-organized their research plans to focus on other tasks they could complete in the meantime. But as the development of the pandemic remains uncertain, they now must think about alternatives to conduct face-to-face focus groups in order to proceed with their project.

Online focus groups provide a way out of this situation. Many researchers might be hesitant to use qualitative online methods that are not well-established yet. As part of my current research, I conducted both face-to-face and synchronous text-based online focus groups, implemented in the form of web chats. This approach helped me to explore relevant methodological advantages and disadvantages. Based on this experience, I identified key aspects to consider during the preparation and implementation of synchronous text-based online focus groups. These include the size and composition of the groups, the discussion process, the moderator’s lack of control, and technical issues.

With respect to group composition, an obvious benefit of online focus groups is that people from different locations can be brought together. In my study, the focus groups were composed of participants from all over Germany, which would have been doable in a face-to-face setting. The online setting instead allows for the participation of target groups that are otherwise difficult to reach, such as physically disabled persons or people living in rural areas. Further advantages result from this mostly anonymous environment including that participants felt more comfortable discussing sensitive topics, and potential power imbalances became less influential.

On the downside, it is difficult for the moderator to manage the discussion due to the synchronous nature of the discussion process. The lack of visual and vocal cues aggravates this problem and makes it hard to capture feelings or moods. I experienced that participants who type rather slowly found it difficult to keep up with the pace of the discussion. Some were still formulating answers to a question, while the discussion had already moved on. Another major issue is information threading, meaning that the group discussion splits into parallel conversations on different topics.

The moderator’s lack of control also extends to the discussion environment. After one session, I noticed that one respondent had copied and pasted a statement from a website as a response to one of my questions. This was something that previous research accounts of focus groups had not prepare me for and could lead to serious problems for the validity of this method. In my article published in the International Journal of Social Research Methodology, I elaborate on these aspects in more detail and provide recommendations on the selection of suitable chat software to reduce the risk of technical issues and disturbances. It is important to keep differences between online and face-to-face focus groups in mind; but with good preparation, some disadvantages of remote discussions can be overcome. Synchronous text-based online focus groups are a method worth exploring – not only in times like these.

Read full IJSRM article here.

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Why Questions Like “Do Networks Matter?” Matter to Methodology: How Agent-Based Modelling Makes It Possible to Answer

By Edmund Chattoe-Brown

“Scientists tend not to ask themselves questions until they can see the rudiments of an answer in their minds. Embarrassing questions tend to remain unasked or, if asked, to be asked rudely” -Peter Medawar.

Disciplines and research methods are often arbitrarily divided by the assumptions they make about the social world. Economics is based almost exclusively on its own definition of rationality which is a minority interest (and widely regarded with scepticism) in almost all other social sciences. Statisticians focus on finding “big picture” patterns in “usual suspects” variables while qualitative researchers emphasise the role of agency, interaction, and context. While this state of affairs may be adequate under the normal academic divisions of labour, it creates a particular problem for interdisciplinary research and research intended for policy. In interdisciplinary research, different (and often entrenched) assumptions must somehow be reconciled so that the outcome really is collective insight rather than simply a ragbag of disconnected “business as usual” sub-projects. In policy research, we need to be confident of all the things that actually seem to reduce crime, not just the subset that criminologists (or economists or sociologists or statisticians or ethnographers) decide that their field should attend to.

But if we want to address this problem scientifically, we need an approach that can represent different organising beliefs about the social world fairly and effectively (which quantitative and qualitative approaches, for example, notoriously cannot do with each other’s insights). If we can represent two different views of the social world using the same framework, we can then examine how much difference it makes if we assume one thing rather than another. The argument of my article (after laying out the nature of this problem) is that a form of computer simulation known as Agent-Based Modelling (Chattoe-Brown 2019) can be developed to offer such an approach. Agent-Based Modelling is increasingly recognised as a technique that offers distinctive advantages to social science in representing process and fundamental heterogeneity (not just in “variables” but also in behaviour) and  in analysing systems where simple individual interactions can lead to counter-intuitive aggregates, so-called complex systems displaying emergence (Chattoe-Brown 2013). This representational richness, based on describing social processes explicitly, allows the technique to avoid “technical” assumptions (made purely on analytical grounds) and to focus instead on the effective use of different sorts of data to justify building models in one way rather than another. (It is thus not only the technology that is distinctive but its associated methodology and relationship with different sorts of data.)

Therefore, most of the article is devoted to laying out and analysing a “worked example” concerning the social aspects of disease transmission, illustrating how Agent-Based Models operate in general and how they can be designed to answer the kind of questions that separate different fields of research. For example, does the presence or absence of social networks “matter” to the behaviour of systems? Some areas (like Social Network Analysis) take it for granted that networks do matter while others like large scale statistical analysis (with no less empirical success) analyse social behaviours without reference to network variables. To address this question, then, we can design an Agent-Based Model In which the social network can be “switched off” while all other aspects of the social process described remain the same. Any differences in the resulting behaviour of the system, therefore, necessarily arise from the presence (or absence) of social networks alone. We are effectively controlling for model assumptions independently. The result obtained from analysing this example is that static social networks matter considerably to the dynamics of disease transmission while evolving social networks make little additional difference. (Like a lot of social science, these results might be considered unsurprising with hindsight but that tells us more about hindsight than it does about the social world!)

Although the article uses the single example of networks as an aspect of social process, another aim of the article is to point out that many important social science debates tend to hinge on mere assertions endorsed by different disciplines which this approach could make a constructive contribution to addressing. For example, is decision behaviour rational, adaptive, habitual, or imitative as different disciplines assert? This debate is unlikely to progress scientifically without a technique for exploring how different kinds of decision making may give rise to distinctive patterns in data that we could discover. The same applies to the opposition between the statistical quest for “big patterns” and the qualitative emphasis on detail. Can suitably designed variants of Agent-Based Models show when “detail matters” and when it may “wash out” to leave big patterns? This sort of approach would be particularly valuable in analysing educational attainment, for example, where individual, interactional, and structural elements are all clearly in play. Being able to move these different positions forward from a “is, isn’t, is too” style of argument should be a major contribution to interdisciplinarity and more effective policy.

Of course, since writing this article, the importance of being able to draw on the best evidence from all relevant disciplines and methods has been made hugely more topical by the COVID pandemic. To tackle a real problem (which in this case is literally a matter of life and death), we need ways of understanding how geography, networks and social behaviour interact with diseases, the physics of PPE and surface contamination and many other aspects of the social process (like who cares for children when schools are closed). Simply biting off parts of the problem using existing approaches and studying them in isolation will almost certainly not be enough to produce effective policy. This article thus shows yet another way in which Agent-Based Modelling can make a distinctive contribution to advancing social science.

See full IJSRM article here.

References

Chattoe-Brown, Edmund (2013) ‘Why Sociology Should Use Agent Based Modelling’, Sociological Research Online, 18(3), article 3, August. doi:10.5153/sro.3055

Chattoe-Brown, Edmund (2019) ‘Agent Based Models’, in Atkinson, Paul, Delamont, Sara, Cernat, Alexandru, Sakshaug, Joseph W. and Williams, Richard A. (eds.) SAGE Research Methods. doi:10.4135/9781526421036836969

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The co-productive imagination: A creative, speculative and eventful account of co-producing research

By James Duggan

What does it mean to co-produce research? The term is used so extensively and diversely that it might be considered merely a convenient buzzword used at the intersection of academics, funders, and communities. There is an extensive series of justifications for co-producing research with communities. Co-producing research, for example, empowers, emancipates, enacts equal and democratic relationships, and aligns with rights-based discourses. Despite these noble aspirations there is a long-standing critique that co-production reproduces the academic or elite power relations it claims to unsettle, whether as tyranny, governmentality strategy, or regulation. A consensus position is that co-production is the space, discourse, and practices that allow us to unlearn and re-imagine research beyond the inheritances of academia as a society of letters. What grounds and commitments might help us navigate the critique and work towards worthwhile aims in collaboratively researching across and beyond the boundaries of the campus?

The co-productive imagination is inspired by speculative and process approaches to explore ways of theorising and practising collaborative research that are adequate to understanding the complexity of the world. Following A.N. Whitehead, this approach seeks to continually question academic abstractions that may result in our minds and inquiries following familiar grooves. Instead, co-production becomes an imaginative act where we iteratively develop propositions – encounters with new ways of feeling and thinking – and then we cultivate our imaginative capacities to understand what potentials are made possible in this situation. Although including concerns of empowerment and equality the focus becomes the creative realisation of events, which are understood as new ways of thinking and feeling that changes our orientations to the world.

The focus of the article emerges from the Loneliness Connects Us youth co-research project which explored loneliness with young people through arts-based and creative methods. I describe my slow and eventful realisation that one of the youth co-researchers was playing a crucial role in co-producing the project aim of creating a space in which we could explore loneliness ethically, productively, and with care for one another across difference. The way this finding came about questioned any claims I might make for co-production as equality, empowerment, or democracy. Instead, it justified thinking about the imaginative processes and practices of doing the research and realising that something matters! Drawing on speculative and process approaches, the article identifies a series of practices and commitments – appetition, techniques of relation, patterned contrasts – that work towards eventful realisations. It is, of course, important that in the shift from co-production as equality to co-production as eventful realisation that young people are not marginalised in research in pursuit of what thoughts and feelings are interesting. Yet, it is equally important to not let abstractions of co-production fix the ways in which we develop research. The aim therefore is not to lose young people but rather to fold commitments for young people with an ethics of the event, finding and tracing multiple and eventful contributions, collaboratively creating new propositions and possibilities to re-imagine a world in process.

See full IJSRM article here.

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Statistics anxiety: Busting the ‘anxious women’ myth?

By Dr Vicky Gorton and Dr Kevin Ralston

For many students, Statistics = Anxiety. This anxiety is often characterised as limiting students’ engagement with statistics and impacting on their performance on quantitative methods courses at university. The relationships between age, gender and statistics anxiety are some of the most examined in the research literature. A survey of these findings might lead us to reformulate the Statistics = Anxiety equation to read: Statistics + Women => Anxiety, as previous research has tended to identify women as more likely to experience anxiety and at greater levels. 

In our article, ‘Anxious women or complacent men? Examining statistics anxiety in UK sociology undergraduates’, we wanted to revisit the core demographic variables of age and sex to examine their association with reported anxiety of statistics. Unlike most other research in the field however, we modelled an interaction between these two variables. This allowed us to explore whether reported anxiety of statistics varies within and between sexes by levels of age (comparing under 25s and over 25s). 

The research is based on a secondary analysis of a dataset on the attitudes of sociology and political science students towards quantitative methods. These data, gathered by Williams et al. (2009) and shared on the UK data archive, are amongst the most comprehensive ever collected on attitudes of undergraduates to QM. Crucially, for our aims, the students were asked whether they felt anxious about learning statistics. This made it possible to interrogate these data to explore in detail the relationship between age, gender and anxiety of statistics. 

The methods we used for the analysis are the same general techniques that many social science undergraduates will learn about during their own quantitative methods courses – logistic regression models and bivariate analysis. Our paper provides a simple applied account of these methods, which would be a relevant example in learning-teaching settings. 

The results indicate that it is older men, not women, who are most likely to report experiencing anxiety of statistics in social science contexts. This is only apparent when considering the interaction between age and gender, without this interaction there is no difference between men and women in the likelihood of experiencing statistics anxiety. 

It is therefore possible that young men, who are less anxious, have driven the gender differences that have previously been reported in research. This is to say that, rather than experiencing excessive anxiety, women may seem more anxious in previous studies because of their comparison to a group of more complacent young men. 

The results call into question the potentially damaging ‘anxious women’ narrative that predominates the literature on the teaching-learning of maths and statistics. We suggest that this paradigm may be misleading, distracting, and an oversimplification. Despite the research focus on statistics anxiety, there is no strong evidence that it has a meaningfully negative influence on the learning of statistics for those on social science courses. By comparison, the pedagogical implications of an issue like complacency in this context has received little consideration. Overall, we argue that it is time to move away from the perception that women studying social sciences are excessively anxious of statistics. Our findings strongly suggest that this is a myth in need of busting.