When I was doing my PhD, someone at a conference suggested that I check out a book called “Trust in Numbers” by Theodore M. Porter. I had gone straight from fieldwork to the conference, and was dealing with the reality that the results were not really relevant to what I had proposed talking about when I submitted my abstract. I was honest, explained that I didn’t really know what to make of it, and the audience members kindly helped me out. I owe them a debt of gratitude because I devoured that book, have since recommended it to countless colleagues, and often find myself coming back to its central theme when I am thinking about my work.
Why did it speak to me so clearly at such a confusing time?
Porter’s book is an unpacking of our collective push to quantify the world. It looks at how we arrived at a society where quantitative reasoning is dominant, and questions if this approach, extended from the physical sciences, is really a useful way to understand our social worlds. He outlines how we are pushed towards quantification as a way to demonstrate objectivity and impartiality. Reading this book was the moment where I realized that framing the world in quantitative terms can therefore be a political exercise, and indeed, not as impartial or objective as we pretend it to be. (noting that there are of course very useful ways in which quantitative research helps us to understand. The point is that it should not be the only way, and should not be viewed as somehow more legitimate than qualitative understandings).
My introduction to this book came while I was studying my PhD as the sole (qualitative) social scientist in a research project comprising geochemists, epidemiologists, soil scientists and hydrologists. My research topic was about naturally-occurring arsenic in groundwater, and how its occurrence intersected with use of that water (e.g. drinking, irrigation) and subsequent policy responses. The results that I was so confused by at the conference were showing me that the authorities in Hungary (my case study country), were aware of the necessary policies, had options to remove the arsenic from drinking water, but were questioning the risk and problem framings around the arsenic in the water. The EU policy of 10ppb arsenic in drinking water didn’t fit within the way that they were framing the risks, the cultural value of the water, and the deeper framing of the role of the EU (you can read more here, if you want).
Both in my role as a researcher in the project, and through the topic I was researching, I was experiencing first-hand the impacts of this ‘Trust in Numbers’, how it positioned me and my role in understanding the world, and was translated into policy.
What has changed since then?
In the decade since graduating my PhD, much has changed in the way we approach the role of social science in environmental issues. For example, I now get to lead a whole social science department, embedded within the global change research institute at the Czech Academy of Sciences. That this department exists, and works closely with our other departments, is a real commitment to interdisciplinarity. And we aren’t alone – the last 10 years has seen a proliferation and strengthening of such centres, and European funding (and therefore national funding) calls usually demand interdisciplinary teams.
However, something fundamental hasn’t changed. Myself and colleagues routinely find ourselves explaining what social science is, having to defend the approaches we use (especially qualitative!), and being framed as being ‘in service’ to the physical sciences. We are the add-ons, the ones who are supposed to translate into policy, or communicate to the public, rather than as having valid research questions ourselves. Recently, at an event on dealing with complexity for building back better (post Covid), the discussion came round to the need for meaningful interdisciplinarity. When I lamented that “we’ve been saying this for the whole of my career, and its depressing to still be saying it” the response was “maybe the problem is that nothing has actually changed in the system”.
What hasn’t changed?
We are still primarily stuck in quantitative framings of problems, quantitative explanations and quantitative solutions. Climate change is a good example. We know what is happening, and we learn from models and projections about what is coming. These are getting ever more sophisticated, and it is important information. It adds a weight of evidence. And this evidence is, importantly, quantifiable, and (largely) seen as objective and scientific. Perfect.
But we are also stuck in a path dependency where in the mainstream (outside my academic bubble), the problem is framed only as being about these models of heating and impacts. I do not disparage this knowledge, we need it. But If a scientist is spoken to (by e.g. the media), it’s a physical scientist who knows about the impacts or the process. If we are only asking people about impacts and processes, then we get stuck in this looped conversation that never progresses into the space of solutions, or how we change systems (or why systems need changing). When we do ask these scientists about ‘what we can do’ there are two options of the reply:
1) someone gives their opinion with borrowed authority, not based on evidence and research (at best, this answer will include something about needing political will);
2) the solution comes from their worldview, and therefore is largely about technology or a further extension of the market (e.g. carbon credits).
I concede that perhaps this explanation sounds simplified, harsh or overly frustrated. But its because it matters.
Why does it matter?
We need to shift the conversation and the problem framing. I loved this short video by Emily Atkin on CNN this week, arguing that climate change needs to extend beyond the domain of the environment reporters, and be on everyone’s beat. I have also seen discussions on Twitter that maybe framing climate change as a health issue would help communicate the urgency and cross-cutting nature of the problem. I agree with all, because they are challenging the way we are framing and communicating the problem, and therefore shifting who needs to be part of conversations and solutions. There is increasing scientific consensus that the underlying driver of sustainability problems is our capitalist system, and therefore economic and social transformation is necessary to avert climate and biodiversity disaster. What this transformation is, how it works, and how to steer it is therefore what we need knowledge on.
However, if we start talking about systems change, political change, economic change, this is challenged by some as being not objective nor scientific.
I dedicate my energies to understanding governance systems, how they frame problems, how they (don’t) implement targets and policies, and how this (doesn’t) match to the physical and social environment. My research tells us how and why governance systems are failing to act on sustainability challenges, and often point towards the system paradigms and structures as being the root cause of these failures. Yet to comment on this, and to suggest ways this could change, is often seen by those outside my discipline (including paper and grant reviewers) as political at worst, or subjective at best. We can quantify what the failure is, and we can quantify the impacts. But the understanding of how we might begin to shift our social constructions away from creating this failure is not easily put in the language of numbers.
So perhaps the start of systems change needs to come from our knowledge systems; what knowledge cultures we listen to, who gets to set the agendas and the framing of problems, and who gets to speak. I don’t just mean academia, though it’s a good place to start. There have been numerous papers recently (and a special issue here) on reshaping the role of universities to address sustainability problems. These often challenge the idea of objective knowledge, and question the cultures that have pushed us into separating ourselves in our ivory towers. I would extend these conversations further, and suggest that we consider the extent to which our trust in numbers is excluding the disciplines that should help us to frame and understand problems like climate change and find solutions.
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