The Social Aspects of Environmental and Climate Change

Institutional Dynamics Beyond a Linear Model

E. C. H. Keskitalo

• Publisher: Routledge
• Year: 2021
• ISBN:
  9781000532593
• Edition: 1
• Topic: Biological Sciences
• Subtopic: Global Warming & Climate Change
• Index: Biological Sciences

The Social Aspects of Environmental and Climate Change critically examines the prominence of natural science framing in mainstream climate change research and demonstrates why climate change really is a social issue.

The book highlights how assumptions regarding social and cultural systems that are common in sustainability science have impeded progress in understanding environmental and climate change. The author explains how social sciences theory and perspectives provide an understanding of institutional dynamics including issues of scale, possibilities for learning, and stakeholder interaction, using specific case studies to illustrate this impact. The book highlights the foundational role research into social, political, cultural, behavioural, and economic processes must play if we are to design successful strategies, instruments, and management actions to act on climate change.

With pedagogical features such as suggestions for further reading, text boxes, and study questions in each chapter, this book will be an essential resource for students and scholars in sustainability, environmental studies, climate change, and related fields.

1

Aim and scope of the book

DOI: 10.4324/9781003043867-1

Introduction

How a research problem is framed is of crucial importance.

In the policy research field, there is a great deal of research asserting that framing a problem is actually the first – and often most crucial – step in determining how to solve it, what actors are important for solving it, and how this should be done (e.g. Schön and Rein 1994).

As a result, many of the struggles in the policy arena involve framing. For instance, should a flood event be seen as a result of climate change or just as a freak accident? If it is framed as a result of climate change, this might mean that there is a need for more far-reaching actions, for instance flood-proofing policy, avoiding building in low-lying areas, and the like. If it is framed as a freak accident, however, the focus might be placed more on direct emergency response after the event, with no need for costly additional actions or inclusion in policy. These types of storylines can thereby serve to promote different understandings of a problem (Hajer 1995).

Thus,

to frame is to select some aspects of a perceived reality and make them more salient … in such a way as to promote a particular problem definition, causal interpretation, moral evaluation, and/or treatment recommendation for the item described.

(Entman 1993: 52, quoted in Weaver 2007: 143, italics in original; see also Reese 2007; Zhou and Moy 2007)

In the same way, the argument in this work is that the framing in research plays a large role. If an issue is seen mainly as one of gaining better knowledge about the environment per se and improved technology, the focus will be placed on this: better natural science knowledge, stronger technology development. However, if it is also seen as one of how present systems can manage implementing the decisions needed (for instance, for adapting to climate change or limiting invasive species spread), the focus will be another.

Some of these issues of how framing occurs may result in long-term and potentially costly misframings. For instance, the focus on gaining better knowledge about the environment per se has been strongly emphasised in the framing in the largest scientific assessment on climate change, the Intergovernmental Panel on Climate Change (IPCC) reports. Largely, the assumption has been that knowledge will lead to action. However, in reports from both 2007 and 2014 (see e.g. IPCC 2007, 2014) it is finally acknowledged that “simply producing more and better knowledge is not sufficient” (Mimura et al. 2014: 887) for achieving policy change.

This understanding, and a criticism of the notion that better scientific knowledge will automatically lead to better policies, is a crucial focus in this book. The assumption that better scientific knowledge will automatically lead to better policies is a crucial component in the disproven linear model of expertise, or linear model of scientific knowledge as it will be referred to here.¹ This is a complex of assumptions in which mainly natural science knowledge and technological development are seen as automatically leading to change, in a way that is rational from a scientific viewpoint (see Text Box 1.1). It has been recognised as regularly applied in large-scale research assessment programmes and assessments, as quite simply “the way science is practised”.

Text Box 1.1 The linear model of scientific knowledge

“Linear models of scientific knowledge transfer have been labelled as ‘technocratic’; they propose that scientific knowledge can be directly applied to practice without any problems or changes. Science helps to increase the effectiveness and efficiency of practical decisions, and scientific knowledge leads to better policies and ‘evidence-based’ policy making. If scientific facts are available, then this availability automatically leads to the use of science in practice. In linear models, political actors demand scientific knowledge, and it is supplied by the science community: this knowledge flows directly from science into practice, in which it is utilised by political decision makers and stakeholders with the aim of producing ‘rational’ solutions. Decisions are then based on scientific information without being altered by the policy process or practical considerations. The linear model of scientific knowledge transfer is still highly relevant among natural or climate scientists who, critically, ask why political actors or society as a whole do not follow their recommendations” (Böcher and Krott 2014: 3643).

Critics note that the pervasive application of the assumptions in the linear model of scientific knowledge needs to be explicitly identified and problematised, as it otherwise leads to acting on incorrect assumptions regarding how society works. Criticism of the linear model has focused on the fact that it ignores the notion that science cannot usefully be conceived of without also understanding society (Beck and Mahony 2018; Briggle 2008).² Critics also highlight that scientific knowledge, in actual life, is not automatically taken up and translated into action; this is because, among other things, policy-makers have to be responsive to very different types of input of which science is only a single, and often relatively minor, actor (De Koning et al. 2014). Real-world analyses have shown that scientifically “rational” decisions are not the most rational ones for actors who may instead follow their self-interests; this means that the scientific results may not be seen as useful or meaningful in relation to their situation (Böcher and Krott 2014). Rather than a notion that gaining use of knowledge may only be about removing “barriers” to scientifically “rational” decisions, policy processes and the actors within them may thus have entirely different goals, understandings of pertinent issues, and motivations (Grundmann 2009).

The linear model thus rests on an incorrect understanding of the policy process. The fact that the model – despite this criticism – is still used has led different authors to see it as “undead” (Durant 2015: 17), as an “ideology” (Grundmann 2009: 402), or as a “myth” (Briggle 2008; Pielke 2007).

There have also been attempts to rework the model. To attempt to address the concern that science does not take into account social considerations, a focus on including stakeholder participation has often been added to assumptions that are in line with the linear model in scientific programmes and assessments (Beck 2011; Durant 2015; Pielke 2007). However, also this addition carries with it numerous considerations. Just like the linear model assumes a removal from society, participation that simply assumes direct and clear deliberation with stakeholders – that they would in fact act similarly to how politicians are assumed to act in the linear model, working with science in a clear and “rational way” focused on scientific priorities – has proven to be incorrect (e.g. Philips 1995). Criticism of this type of focus includes, among other things, the assertion that real-life deliberation is never unconstrained and that those arguing for it in a simplified, unproblematised way may instead increase the influence of already powerful actors, without reflecting many actual societal divisions and consequences of decisions (Durant 2015; Keskitalo and Preston 2019).

Despite all this criticism, this model of a mainly natural science development that today includes societal aspects by means of stakeholder participation, for the purposes of decision support, remains in almost general application (Beck 2011; Durant 2015).

This book takes its point of departure in the notion that this misunderstanding of the social, political, and economic world in this way remains a major – and perhaps the largest – obstacle to correctly understanding social environmental research and its contributions.

This is because, in fact, in the faulty linear model, there is no need to understand social, economic, and political considerations – institutional dynamics – through research, as the social, economic, and political actors are assumed to automatically relate to and implement best (natural science) knowledge. But because they do not do this, the model does not work and the processes that apply this model are left without the means to integrate the research on social, economic, and political actors and worlds that are in fact needed to conceive of change.

In this, the climate change field is by no means an exception. Climate change adaptation and mitigation, as well as environmental problems in general, are crucially issues of framing. The field of climate change research has largely been formed by its origins in impacts-based scenario research, and it is still often undertaken in the format of, for instance, integrated assessments or vulnerability assessments, which often focus on natural science components with added stakeholder participation, largely using modelling and scenario-building as decision-support tools (e.g. De la Vega-Leinert et al. 2008; De la Vega-Leinert and Schroter 2009; Noble et al. 2014; Beck and Mahony 2018; Malone and Engle 2011 for an overview). At the same time, there has been a criticised consistently low involvement of the social sciences and the humanities (Victor 2015; Stern and Dietz 2015) – and as noted earlier, only recently has the IPCC, based on this data, started clarifying that knowledge is not enough.³

What this book does

This book challenges the assumption that only a limited range of social sciences and humanities research would be relevant for understanding environmental issues such as adaptation and mitigation to climate change – including why mitigation and adaptation often do not take place.

Climate change mitigation regularly refers to what has to be done to limit emissions, while adaptation refers to what has to be done to deal with the changes that will take place – even if we were able to halt emissions today.⁴ Adaptation thus includes, for instance, strategies and actions for dealing with changes in temperature and precipitation such as seasonal shifts, changes in how much rain we get when and where, and extreme events like storms and floods. It also includes recognizing and responding to the effects of these sorts of changes, such as changes in production (e.g. food production), impacts on water, pest outbreaks, or the spread of invasive species (IPCC 2014).

Thus, adaptation will be needed almost everywhere: such as in how to build to withstand floods, dimension sewer and water pipes, provide electricity even under storms, and produce food in a changing climate. Therefore, while the focus in adaptation research has often been on the local level, the role of adaptation is by no means limited to a local focus. Instead, these types of actions need to be decided upon and undertaken in virtually all governance systems, making adaptation an intensely social and complex question (e.g. Keskitalo and Preston 2019).

While many examples in the book will, for these reasons, be taken from the adaptation field, the discussions here regarding the role of the social system and transitions within it are equally applicable to mitigation as well as to broader environmental problems. While examples will be taken from, for instance, assessment work that summarises the literature, the treatment of social issues in these examples can be seen as symptomatic of larger fields such as “sustainability science”, energy research, integrated assessment, and the like (e.g. Sovacool 2014). The book’s focus is thereby not as much on understanding only one issue, or criticising only one literature or report, as it is on the fact that framings that build on the linear model are pervasive to multiple bodies of literature. Literature on climate change is an example, as are specific reports, but the linear model can be found in multiple bodies of literature with the same problems. The hope is that, through the illustration of these issues, the reader will become aware of the components of the linear model and be able to distinguish these in whatever field they occur in – and will then also be able to contrast them with other, more social framings.

To this end, the book itself thus constitutes a “framing”, directly contradicting the framing in the still-influential linear model of scientific knowledge. The framing in this book focuses on understanding the real-life institutions that need to respond to, and have indeed created, the climate change problem. The focus is placed on understanding climate change adaptation (and, by implication, mitigation and broader environmental issues) through a framing focused on institutions and institutional aspects.

The book can thereby be seen as providing an institutionalist framing of the problem of adaptation, with the assumption that if this logic can be understood, climate change and environmental issues will also be seen and analysed in a different way (cf. Beck 2011). The aim is to forward this framing and what difference it makes in viewing climate change adaptation compared to how it is often done in literature (e.g. Victor 2015; Stern and Dietz 2015; Noble 2019).

On this basis, the volume illustrates that adaptation and mitigation considerations are necessarily implemented in an existing social structure with historically established institutions, and that it is through understanding the breadth of research on these topics that we can understand how to design strategies, instruments, and management actions for the future.

Understanding climate change and society – or environment and society – is thereby not only about limits and barriers, or other means that to some extent black-box societal processes (e.g. IPCC 2007, 2014). Rather, it is about understanding the foundational role played by research on social, political, cultural, behavioural, economic, and political processes in understanding the institutions through which adaptation and mitigation need to take place – if they are to happen at all.

Understanding this means that literature and approaches relevant to understanding – for inst...