Geography’s contribution to the Sustainable Development Goals

Abstract

Building on Liverman’s critique of the Sustainable Development Goals (SDGs), I argue SDGs must be conceptualized as situated by (i) unpacking the black box of social, political and intellectual consensus behind indicators and (ii) reimagining development goals as dynamic performances that are uneven over time and space for both populations and individuals. Poverty, justice and other targets of SDGs are not a state of being but rather a punctuated experience for the individuals and populations in question. For the SDGs to be effective, they need to go beyond simple statistics to account for how situated, performative aspects of lives evolve, rather than as they are.

When asked to participate in this dialogue, my first thought was, ‘Millennium Development Goals (MDGs) and Sustainable Development Goals (SDGs) are slippery things, how can one disagree with justice, equality and environmental sustainability?’ Given the history of critiquing development (McDowell, 1993; Rocheleau et al., 1996; Watts, 1983; Yapa, 1996), myself along with many critical geographers find engaging with indicators and entrenched development technologies to invoke a sense of unease, or at least ambivalence.

As Diana’s essay points out, adopting these laudable goals is not straightforward. SDGs and MDGs simplify and render legible complex processes of social and political reproduction. They serve to privilege statistics and measurement as the ultimate evaluation of whether the world is moving towards sustainability (Robert et al., 2005). Diana reviews how we can understand this as a proliferation of biopolitics or attempts by various authorities to govern and control through making populations legible (Escobar, 2011; Gabay, 2012; Li, 2007). What is interesting about the SDGs is the incredibly sweeping domains they map out as necessary of evaluation. Millions of dollars will be spent and thousands of projects will be implemented in the name of fulfilling them. Similar to the MDGs before them, SDGs reshape how development practice is done and more nefariously, how we imagine the world ought to be, distilled into numeric form (Ilcan and Phillips, 2010; Saith, 2006).

I want to pick up from Diana’s essay and argue that in addition to deconstructing the indicators and statistics employed, we also need to tackle the problem of consensus science. The SDGs in particular were built upon a desire to bring together different dimensions of development into an encompassing framework. The scientists and practitioners who worked on articulating the goals were given the task of agreeing. As a result, this consensus reflects a process of homogenization, at least intellectually (Klenk and Meehan, 2015). It required people to listen and take on board other ways of framing a problem and by necessity, shifting their own intellectual stance. Fiercely contested ontological politics and social relations have been transformed into colourful Lego blocks with compelling logos. Remnants of those contestations persist in the bewildering array of subtexts that attempt to nuance and capture different interests and ontologies within each goal. And while these efforts at representing diversity should be applauded, standardized goals, agreed upon by consensus, can never reflect the diversity of visions for how to live well that exists across the world (Beck et al., 2014; Jasanoff, 2013). Furthermore, they may be distracting us from moving towards more a more just, sustainable world.

Deconstructing consensus science requires prising open the black box of their formulation to understand more clearly what kind of consensus they represent (Goldman et al., 2011; Hulme and Mahony, 2010; Latour, 1987). An ethnography of this form of authority/knowledge-in-the-making will help illuminate how and where geographers might more effectively intervene. It would be revealing to examine who was involved in articulating which goals, at what point in the process they were brought in (or edged out) and what kind of debates led to consensus. This is never an innocent process of dialogue. Rather, social differentiation such as gender, class, nationality, age, academic achievement and a variety of other intangible social differences are at play within these dialogues to shape whose voices are loudest. Here the project is not to name and shame our colleagues who engaged in formulating the SDGs but rather to understand the disciplines, institutions, ontologies and geographies of the people who came together to articulate the goals (see Beck et al., 2014; Mahony, 2015, for example in relation to the Intergovenmental Panel on Climate Change (IPCC); Hulme and Mahony, 2010). Many of us who have worked with large research teams know that confrontational or clear intellectual positions are counterproductive to the functioning of a team. Intellectual disagreements can be difficult to keep emotionally separate from personal attacks, and insisting on a particular position can thwart short- and long-term collective research goals. In my experience, this usually results in controversial members being quietly deleted from email circulation lists, their contributions being edited out, or people voluntarily stepping away to allow the rest of the group to continue. A qualitative investigation into how particular goals came into being would help to situate the Lego blocks within the politics of their articulation.

Second, consensus science cannot provide an intellectually reliable foundation for analysis. Exposing how and why this is the case is important when unpacking development goals. While the definitions and domains that emerge from consensus science are useful as an overview, to map the terrain of a debate or to broadly frame a problem, like climate change adaptation or development, they cannot easily be used as analytical tools (Mahony, 2015). Translating broad frames into indicators at best masks the diversity of analytical stances within a descriptor and, at worst, privileges the analytical stances most conducive to quantitative measurement. Indicators require distilling complex processes down to a couple of measurable instances that can somehow capture the essence of those processes – or at least how they are changing over time.

Diana captures part of this critique in her elaboration on the problem of getting the targets right. There is politics to the science and practice of which targets are chosen and how they are represented. But I want to push this a bit by conceptualizing targets as performances rather than objects. It’s not so much criticizing whether the right targets have been identified, as it is to tackle the problem of how we imagine what targets (i.e. poverty, gender equality, etc.) are. As the SDGs are presently formulated, they demand that countries improve their indicators by specified percentages within a fixed time frame. For example, they frame poverty as a state of being measureable by annual income. Yapa (1992), over 25 years ago, argued that maps of gross domestic product (GDP) present a skewed view of well-being that suggests increasing GDP is good in itself. Diana similarly draws out some of the problems with these indicators and how aggregate measures mask deprivation within countries, communities and households. However, her critique continues to operate within the frame of a measurable state of being. In some respects, she is arguing that we need to get the measurements right rather than challenging their measure-ability.

I want to begin my critique by insisting that poverty (or justice, gender equality, etc.) is not a state of being and, as such, is not conducive to static measurement. Poverty is a series of performances and interlocked processes that serve to render one ‘poor’ (discriminated against, lacking resources, etc.) (Escobar, 2011; Yapa, 1996) at particular moments in time. It is not a state of being, but rather a punctuated experience for the individuals and populations in question. I have arrived at this understanding based on the earlier critiques referenced and my own experiences of living in communities that are classified as poor. I absolutely agree with the critique Diana invokes that homogenizing communities or households as all equally poor serves to reinforce hierarchies based on age, kinship, gender, race, disability and other dimensions of social inequality. But I also see that ‘poverty’ is not even across time and space for individuals and populations (see also Yapa, 1996). There is often a seasonality to poverty linked either to agricultural or work availability cycles. People are ‘poor’ at some times during the year and at other times have excess income and resources that can be invested. Yet those investments cannot buffer them against the deprivation they know they will face later in the annual cycle.

In addition, poverty is situated. When at home, within communities, many people experience poverty very differently than when they attempt to move beyond the geographical territory of their place. Well-off families in particular places—defined by access to land, resources, food security and income—find themselves unable to access education, medical care, technology or other services when they move outside of their immediate locality; this is of course most profound when moving internationally from low-income to high-income countries. Another form of situated poverty occurs when new technologies arrive in communities. Peoples’ incomes, which had previously been more than adequate for livelihood needs, are not sufficient to access these new technologies. It is in this sense that I argue poverty is situated and performed. Measuring poverty through indicators fails to capture the essence of poverty, no matter how disaggregated and careful the measurements are. They are too static to account for the situated, shifting experience of being in poverty. If counting does not reflect the reality of being in poverty, it is not an adequate guide for understanding how to alleviate poverty.

My critique insists on the dynamic, performed nature of the processes identified by the SDGs that shift over time and geography. If we conceptualize targets as dynamic, then the SDGs have distracted us from understanding how we might capture a desire for justice and peace (SDG 16), for example, that can be accountable as it evolves, rather than as it is. Justice and peace, similar to my critique of poverty, are enacted, performed, not a state of being or an institutional end point. As such, they are not easily quantifiable, certainly not within simple statistics. While complex mathematics is well outside of my expertise, there are mathematical equations that can take account of processes that change over time and space, that lack fixed outcomes and nevertheless can provide some ‘measure’ of change. Perhaps there is some potential to use these as forms of measurement to avoid static ontologies. I can see good justification for wanting to measure and compare. But these measures make worlds and shape practice as Diana argues (see also Barad, 2007). It is vital that we situate measurement(s), demand that they are always placed in context.

Situating SDGs requires far more than incorporating more aspects of gender inequality, one of the domains where the interventions of critical scholars have been celebrated as particularly important. Rather, it requires unpacking the black box of social, political and intellectual consensus behind individual indicators. Can we imagine partnerships whereby one of us acts as the external critic who can keep alive controversies, which out of necessity are smoothed over by colleagues involved in the consensus politics of the formal processes? And more ambitiously, it requires reimagining development goals as dynamic performances that are uneven over time and space for both populations and individuals. This kind of conceptualization brings the project of development goals closer to lived realities. We need to promote these imaginaries within academic and practitioner circles and take on the challenge of linking this way of understanding development to the practice of development. It is through this kind of contribution that I try to avoid my critical insights being ‘rendered technical’ (Li, 2007) and rather keep open political possibilities for imagining different pathways to a better world.