Fast and slow thinking in trying to make a difference

Janet Bowstead, one of our #DataImpactFellows for 2019, explores how fast and slow thinking could make a difference in creating impact.

 

‘Impact’ is about trying to make a difference: to generate and use evidence to drive changes in understanding, practice and policy.

But what really drives change?

Organisations are commonly encouraged to develop a ‘theory of change’ for their work; or to gain funding for a particular project.  It is often a difficult process – and sometimes the process can be more useful than any particular output – as individuals and teams try to make clear and explicit previously unexamined assumptions and deeply-held beliefs and principles.

Data and evidence have a role in this:

What do we know about the current situation?

How will we measure what we do and what it achieves?

But there is also a role for professional judgement, and different types of knowledge, in tackling complex social issues.

Social issues are multi-faceted, requiring multiple methods of research to conceptualise them, to understand patterns and processes, and to devise appropriate responses.

They are intrinsically political and contested.

This can be a poor fit with a linear model of research impact on policy and practice which assumes that quality research evidence persuades policy-makers to shift their understanding of policy problems and to consider adopting the policy and practice recommendations in research outputs.

Is that really how policy-makers think and act?

Concepts of ‘fast and slow thinking’ can help us with a more nuanced understanding of how to make a difference in the fields of policy and practice.

 

Woman looking up while thinking

Image: slow thinking. Photo by Tachina Lee on Unsplash

 

The linear model of research impact assumes the dominance of deliberate, methodical, rational, calculating ‘slow thinking’ in such decision-making.

However, these different policy and practice audiences may also be driven – consciously or unconsciously – by the ‘fast thinking’ of emotions and stereotypes; which linear models of research impact tend to neglect, as Paul Cairney discusses in his chapter “Evidence and Policy Making.” In What Works Now? Evidence-Informed Policy and Practice.

Evidence can be brought to bear on emotions and gut feelings; but it is generally through different processes of developing insights and understandings rather than a sequential model of responding to research outputs and recommendations.

It is therefore not the data alone which have an ‘impact’, but a more complex and integrated assemblage of existing knowledge and judgement, with new research outputs; and for a range of audiences.

In contrast to a simple linear model of research impact, research influence can be considered as requiring a focus on both fast and slow thinking: on emotions as well as facts.

The research process can be understood as more of a participatory entanglement than a sequential and direct application of research outputs to achieve research outcomes.

Forty years since Carol Weiss’s elaboration of ‘The Many Meanings of Research Utilization’, her characterisation of multiple conceptual and strategic models, in addition to knowledge-driven and problem-solving instrumental models, outlines a complexity that is still relevant to trying to make a difference with research today.


Janet Bowstead is one of our #DataImpactFellows for 2019.

Janet is a Postdoctoral Research Fellow at the Royal Holloway, University of London.

She is a feminist academic with a professional background in frontline, policy and coordination work on violence against women.  Her research is interdisciplinary in nature, across geography, social policy and sociology; integrating quantitative, spatial, qualitative and creative methods.  She has research articles in journals in geography and wider social sciences and social policy.  Janet is currently a British Academy Postdoctoral Research Fellow in Geography at Royal Holloway, University of London.

 

 

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