More controversially, my article argues that this would be a better way to reform research funding than lotteries, which others’ research indicates would be better than current norms. Norms are changing though – one of the things I’ve learnt more about since publishing this article is how the Health Research Council of New Zealand has been using a lottery to allocate some grants. They have been doing that for long enough to publish a peer-reviewed paper about it.
Behaviour change policies, known as nudges, have been used by governments across the world to get people to behave in pro-social ways, such as making healthier lifestyle choices or reducing their environmental footprints. Nudges use behavioural insights to steer people into doing the right thing, while also giving them the choice. Critics argue that traditional nudge policies are top-down, manipulative and un-transparent. Nudge policies seem to expect the worse in people, and are easy to caricature as a technocratic approaches to policy design.
However, a new kind of nudge – ‘nudge plus’ – has started to spring up. Nudge plus tackles the risks of paternalism in traditional approaches through the participation of those being nudged. If nudges are going to be even more ‘bottom-up’, how can such behavioural public policies be developed?
The COVID-19 pandemic has sparked a major debate about the role of experts in policymaking and the capacity of politicians to ‘follow the science’. The trend we have seen, where expert advisers have increasingly become the public face of the pandemic, raises questions about the evolving role of experts in other public policy challenges – including challenges where the scientific base is arguably far clearer about effective policy responses. If politicians are willing to ‘follow the science’ with such diligence in relation to COVID-19, why does the same principle not apply to other public health challenges?
Many of us place our hopes on innovative breakthroughs and groundbreaking discoveries, believing them to be our best bet to achieve a better world. And indeed, science has produced extraordinary breakthroughs. Vaccines radically reduced the risk of death from communicable diseases. Nitrogen-based fertilisers vastly increased the production of food. Computers completely transformed how modern humans learn, work and communicate. Surely, it would seem that investing in scientific breakthroughs is the key to progress. In this spirit, social scientists develop ‘evidence-based’ practices and policies and create hierarchies of evidence to determine ‘what works’. Many believe that if only science can produce enough evidence, discoveries will follow that can change the world – if only we can effectively compel others to accept them.
In a recent article published in Evidence & Policy, we explored the use of Aristotle’s three knowledge types: empirical knowledge, technical knowledge and practical wisdom, in the everyday work and decision-making of frontline public service professionals.
Our qualitative case study of a Scottish local authority revealed the importance of integrating and recognising the different types of knowledge that are needed to respond to complex policy problems, often referred to as ‘wicked’ problems. Understanding the craft of integrating different types of knowledge, and valuing what can be learnt from frontline workers, is key in achieving impactful evidence-informed policy.
In the current context of a rapidly changing policy landscape resulting from COVID-19, making policy decisions informed by the most appropriate types of evidence is crucial. In this blog, we discuss how Aristotle’s knowledge types can help us understand the types of evidence that should be considered in this ever changing landscape.
Matthew Johnson, Elliott Johnson, Laura Webber and Kate Pickett
The COVID-19 pandemic has increased interest in Universal Basic Income (UBI) as a means of addressing a range of socio-economic insecurities. While previous trials of cash transfer schemes have often focused on low-level transfers inadequate to satisfy the needs for which the policy was originally developed, emerging pilots are moving toward a position of increasing generosity. Our multidisciplinary project, Examining the Health Case for UBI, has brought together colleagues in behavioural science, public health, epidemiology and economics to establish pathways to health impact outlined in Figure 1 below. Our work suggests the potential for significant health impact and attendant economic benefit via reduced healthcare costs and increased economic activity. The model suggests that elements of impact may only be felt if payment is set at a more generous level. This could create greater return on investment and, ironically, a more cost-effective system.
We find that the adoption of evidence-based policies in US states is driven more by Machiavellianism than altruism. Although engagement with evidence-based policymaking (EBP) can produce more efficient and effective government, it can also supply new levers of control to politicians and bureaucrats, which can be used to produce electoral benefits. An appeal to EBP can be used to centralise control of executive functions, as well as to manipulate budgets, that incentivise adoption. Further, the construction, purpose and outcomes of these laws are influenced by the institutions, parties and officeholders who craft them. Our study finds that Democratic governors, Republican legislatures and state innovativeness are significant predictors of EBP adoption in the American states.
Especially in times of crisis, the relationship between evidence and policymaking may change dramatically. The current Covid-19 crisis generated manifestations of ‘evidence informed policymaking’ in an unprecedented way, both nationally and locally. It also showed that the need to use internationally organised, reliable data for effective policy interventions has never been more urgent in times of peace. This information needs to be both profound and directly available.
In the processes of shaping evidence informed policymaking, scientists from all kinds of disciplines play a crucial role to substantiate the development of policies. An international, virtual conference taking place 15–18 December 2020 will treat the outcomes of the current crisis as input for the challenge of professionalising the structured interaction between evidence and policymaking. The current learning processes will be analysed in the context of the existing knowledge infrastructure for policymakers. Instruments for creating evidence for policymakers have recently grown with the introduction of Big Data and the development of algorithms. Another widespread trend is the use of innovative evaluation processes in order to enhance the effectiveness of policy instruments and the growth of new standards for experimental policies.
This special issue uses the lens of Creativity and Co-production to explore the meaning of ‘evidence’ and whose meaning counts. It considers what the terms ‘creating’, ‘making’ and ‘production’ mean with regards knowledge creation, sharing and putting into action. It examines the potential role that created artefacts play. For example, what are the values embodied and represented in ‘knowledge artefacts’ and what affordance and agency might they give to human actors?
Areas for discussion include:
What evidence is valid, who produces it, and how was it produced?
What is the process by which ‘evidence’ can be interrogated by others, made sense of, and acted upon?
Not acting on evidence is commonly described as the ‘evidence gap’. Could this be broken down into a series of ‘micro’ gaps between Evidence and Knowledge, Knowledge and Knowing, Knowing and Action?
What role do creative practices, tangible objects, and visual language play in bridging each of these micro gaps?
What does it mean to use evidence in policymaking? This seemingly simple question has been remarkably under-defined in all the calls for increased use of evidence. Indeed, many of those who champion ‘evidence-based policymaking’ do little to explain what it means for a policy to be evidence-based, and have trouble explaining what evidence use actually means when decision makers have multiple competing goals and social concerns. Evidence is simply seen as a good thing – and more use is better – without really considering what that means or what happens when there is disagreement around which evidence to use for what goals.
Policy scholars who study evidence, on the other hand, have approached the issue from the perspective that ‘evidence use’ can mean any number of things within a policy setting. The literature can, therefore, appear divided into two extremes: either evidence use is taken for granted to be a known (assumed to be good) thing, with little consideration of political realities, or alternatively it is seen as multidimensional, the form of which is constructed by the nature of policy ideas, processes, and interactions.