Drawing on a recent article in SPS, and related writings, this blog explores causality as a key concept in social policy research. The need to engage with complex causal processes – with their multiple, fluid and relational elements – is stressed here. Researching complex causality requires dynamic modes of research that can move us beyond a policy focus on what works? to uncover how things work through the stream of time.
Why is causality important? Causality is an exploration of the causes and consequences of change (or continuity) in human affairs. It is our way of making sense of the world. ‘Causes’ are simply explanations, forms of reasoning that give meaning to our existence. In general we want to know how things happen and why events and actions turn out in particular ways. Researchers are commonly expected to offer such explanations; any argument that something ‘influences’, ‘impacts’, ‘shapes’ or ‘transforms’ something else is a causal claim.
Causal investigations have been sharpened over the decades as part of a widespread shift in the focus of social enquiry from structures to processes, from being to becoming. Beyond an understanding of what is, the processual ‘turn’ brings into focus action and reaction, change and conflict – what is evolving, changing, growing, receding or dissipating through time. The nature of the journey, with its fluid twists and turns, its fits and starts, assumes just as much importance as the starting point, or the destination reached.
Causality and Policy Processes. Understanding causal processes is profoundly important in policy contexts where people need to change their practices or adapt to new circumstances, or where the effects of policy interventions need to be monitored and evaluated. Unless researchers are able to talk in cause and effect terms, they may not have much to offer a policy community that is bent on knowing what works? Moreover, without a proper understanding of the journeys that people undertake – the nature of their transitions into and out of poverty or prison, employment or education, health or housing – attempts to support people through these transitions and improve outcomes are more likely to fail.
Simple Causality. The search for causal insights has traditionally been seen as the preserve of predictive, measurement-based social science that views causality in simple linear and sequential terms: if A commonly follows B, then A is likely to cause B. Causality is reduced here to regularity and repetition. Yet tracing events back to a single cause, or projecting forward to one desired effect, is overly reductionist. Causal models of this sort may tell us very little about the complex ways in which events actually unfold. They are too abstracted from dynamic, real world processes, practices and interactions, and the meanings, motives and sensibilities of those involved.
Simple causality and policy. Despite these drawbacks, simple causal models are commonly used to drive policy processes. They are attractive to policy makers because they do not require messy, tailored responses but can be standardised, rolled out en-masse, and their delivery and effects monitored through tick-box precision. However, assumptions that an input will, in instrumental, mechanistic or deterministic ways, lead to a desired outcome may be misguided. For example, there is a growing body of empirical evidence to suggest that measurement-based welfare-to-work interventions are often inconclusive and ambiguous in their effects; they are too narrowly conceived, driven by hard and inflexible forms of conditionality, a penchant for a ‘quick fix’, and a rigid one-size-fits-all approach to how change should occur. Such measures may produce unintended and counterproductive effects. With their fixed tempos and rigid prescriptions, they pay too little attention to how events actually unfold in human affairs and the array of relational and experiential factors that can make a real difference to people’s lives.
Complex Causality. Interpretivist forms of enquiry offer an alternative way forward. In qualitative fashion, they start from the premise that the real world is complex and that lives are shaped through an intricate web of interacting influences that are multiple, fluid, unpredictable and relational. Complex causality is based on the insight that lives do not necessarily unfold in chronological order, through discrete and predictable sequences of change, in one linear direction or at a uniform pace. This means that there is no simple, direct or singular relationship between cause and effect. Influences may run in more than one direction, giving cause and effect a circular, spiralling or random relationship, rather than a straightforward linear one. The logic that A leads to B is transformed where A leads to B leads to A. Complex causal processes have no temporal fixity, no predictable pathway or direction, and no discrete start or end points: the idea of neat beginnings, middles and endings gives way to a sense of endless middles.
Researching Complex Causality. Given this shifting and fluid picture, how then are we to research and understand the complex causal processes that shape lives? This requires some new and creative thinking about research methods and how they may be implemented.
One of the most exciting developments comes from Qualitative Longitudinal Research. This flexible, responsive mode of real-time, real-world enquiry is attuned to the flux of the real world. It seeks to walk alongside as people’s lives unfold, discerning change in the making, and following reality in all its windings. The rich case-study methodology takes us beyond simply what works, to consider how things work, for whom, in what particular circumstances, and in which particular settings and tempos of change. It also enables an understanding of what matters to people and what helps them as a precursor to understanding what may or may not work. Moreover, it is worth noting that moving away from standardised causal models to engage with the rich particularities of lives does not require us to abandon generalisations. Broader insights emerge by piecing together a rich mosaic of data that gains credence through the extent, variety and weight of the empirical evidence base.
A Partnership Model. As a mode of ‘action’ research, qualitative longitudinal enquiry has the capacity to transform the interface between research and policy. Working in partnership with practitioners and policy analysts, and in consultation with service users, this methodology can be harnessed to run alongside an unfolding policy process, not only to chart how things change, but to design, monitor, evaluate and facilitate change as it unfolds.
In this way, impact can be created as an integral part of the research process. In such as process, policy makers can come to see evaluation as a collaborative tool for ongoing improvement and refinement, rather than an unwelcome judgement on their current strategies and performance.
Final Reflections: A Culture of Improvement. In a complex, fluid world, there are no simple causal models or definitive or universal findings, and no ‘quick fix’ solutions for policy makers. Whatever interventions and solutions are put in place are necessarily provisional, the best that may be achieved in current circumstances. Recognising this requires a more modest and responsible approach to policy making, one based on a culture of continuous improvement, transparency, collaborative working with researchers, and an open sharing of knowledge and insight. These are potentially exciting developments that may help to reconfigure the relationship between research and policy. They deserve greater attention in the task of developing research strategies and insights that are attuned to the rich dynamics of real lives, and the ever shifting world of policy making.
About the author
Bren Neale is Emeritus Professor of Life Course and Family Research at the University of Leeds.