In Part Three of my blog series, Diary of a Research Fellow, I discussed some of the ways in which I have been getting my research project established about men’s care responsibilities in low-income localities. In Part Four of my blog series, I reflect in more detail on the process of the Qualitative Secondary Analysis I have been conducting in order to help me to refine my research questions. In particular, I discuss some of the emerging findings of synthesising two qualitative datasets and the benefits of employing a realist methodology for working out the best approach to their investigation.
*Disclaimer these ideas are new and I am testing them out. Any constructive feedback and/or criticisms much appreciated!
In conducting Qualitative Secondary Analysis (QSA) of two existing research datasets from the Timescapes archive, I am doing something quite innovative methodologically. Not only am I situating my research questions and interests in relation to broader existing literatures (relating to men and masculinities, poverty, care and family) but I am also developing hypotheses from these datasets, that my own original empirical project will seek to refine and test. As such, what I am doing is synthesising the two datasets in order to generate a hypothesis that I wish to test and explore about the longitudinal dynamics of men’s care responsibilities.
It has taken me a long time to get to this point and alongside getting familiarised with the datasets themselves, in terms of their content, composition and contexts of production, I have been doing a lot of thinking, reading and discussion with other sociologists to determine the validity of my approach.
Given the relative infancy of re-using qualitative data, there is very limited advice, or indeed critical reflection, about bringing two qualitative datasets together for the purposes of social explanation. Sarah Irwin and Mandy Winterton, of the original secondary analysis project from Timescapes, are a relative exception. They have detailed several ways in which existing datasets might be used productively, including when two datasets are brought together for the purposes of comparison. In one example they outline how they arrived at a set of questions relating to gender and issues of time and work life balance that could be asked across one or more datasets. The advantage of the Timescapes research projects is that they a linked by a shared interest in time, family relationships, identities and generation. They were however, produced by different research teams, from different disciplines, in very different contexts. In debates about QSA (that I summarise briefly in my recent presentation at the BSA conference about the QSA I am conducting) there is a great deal of concern about issues of context and Irwin and Winterton (see Irwin and Winterton, 2012; Irwin, Bornat and Winterton, 2014) are very careful in explaining their methodological approach in terms of the importance of familiarising themselves with the datasets available to them, including developing an understanding of their (multiple) contexts of production. They emphasise the importance of exploring patterning and process within each dataset first and then exploring parallels across the data sets to see if meaningful comparison could be made across projects. Such an approach is an inductive one.
I have found the language of comparison and comparability very difficult for explaining the process I am working through in conducting an analysis across my two chosen datasets; Following Young Fathers and Intergenerational Exchange, so my approach has required a departure from the examples outlined by Irwin et al, while remaining committed to documenting the process. Given the generational position of the participants in each dataset (teenage fathers in one and mid-life grandfathers in the other) the contexts of production for each dataset are related but rather different. Similarly, it has not been possible to explore responses to commonly asked questions of the young men and the mid-life grandfathers, as Irwin and Winterton discuss, given differences in the ways in which the interviews were conducted in each dataset.
Nonetheless, in terms of developing a longitudinal understanding of men’s relationships and their care responsibilities for children and others in contexts of poverty and constraint, bringing the datasets together has been illuminating. A synthesis of the two datasets has been useful because they complement one another; they provide evidence of the longitudinal dynamics and implications for men of partnering and re-partnering, which consequently influence their experiences of providing and receiving care and how they come to be viewed by services providers and policy makers in specific relational contexts. The evidence in the datasets suggest that factors such as partnering, having children, re-partnering and acquiring children and grandchildren and so on have significant cumulative impacts for men over the life course that make it difficult for them to provide the care they express that they want to.
As an example, the datasets reveal that men apparently rescue young women from abusive families. They have children young and they negotiate living arrangements as young people who have become parents, often in the context of their relationships with their own parents and grandparents. From this point on their trajectories diverge. Some stay with their partners through a sense of love, commitment and obligation and a desire to ‘be there’ for their partners and children; other men leave their partners for a number of reasons. Some fight for access to their children (as they do in Following Young Fathers) but this is often difficult to negotiate and manage in a context where fathers are not often recognised or formally supported (both financially and emotionally). Some of these young men discuss getting into ‘trouble’ when they have less access to their children. They may also then go on to re-partner and have more children. In Intergenerational Exchange, there are narratives where these apparent ‘rescuers’ become abusive themselves. The grandmothers in the Intergenerational Exchange study describe the men who they re-partner with as saviours, who rescue them from the abusive angry men they were with before. Via these processes of partnering and repartnering, men acquire and leave behind various care responsibilities, although this is not an entirely agentic process. They may lhave to juggle their previous relationships and care responsibilities with those they acquire in their new partnerships and in contexts of constraint, have to make decisions about where their often limited resources are best directed. The evidence in both datasets suggests that men do care and are invested in their care responsibilities across the life course but that they may face significant barriers and challenges that emerge in the processes of repartnering.
The above explanation or model, describes some of the longitudinal patterns and processes that are in evidence when the two datasets are synthesised for the purpose of social explanation and the refinement of ideas to test. Epistemologically however, rather than conducting a comparison across these datasets, I am instead working with a model of complementarity, seeking to explain what works for whom in what circumstances and why (Pawson and Tilley, 1997; Pawson, 2006; 2013). As Nick Emmel, a realist methodologist explains in his blog, investigation in a realist framework zigzags between ideas and evidence, methods and samples are always chosen in the service of testing, refining, judging, elaborating, …, ideas. Explanation is an effort to work out the relations between ideas and evidence. These methodological ingredients, for describing how to do realist methodology, are guiding my approach, something I have been working out as I bring these two datasets into meaningful analytic conversation.
Irwin, S. and Winterton, M. (2012) Qualitative Secondary Analysis: An Extended Guide, A Timescapes Working Paper, Series No. 7. Available here
Irwin, S., Bornat, J., and Winterton, M. (2014) Qualitative Secondary Analysis in Austere Times: A reply to Henwood and Shirani, FORUM: QUALITATIVE SOCIAL RESEARCH, 15 (1): 1-8.
Pawson, R. and Tilley, N. (1997) Realistic Evaluation, London: Sage
Pawson, R. (2006) Evidence Based Policy: A Realist Perspective, London: Sage.
Pawson, R. (2013) The Science of Evaluation: A Realist Manifesto, London: Sage