Energic Calculations: Using Energy Burden to Prioritize Electrification in Colorado’s weatherization assistance program

Lauren Barrett, University of Colorado Boulder

It is in our homes that electricity is arguably the most entwined with our daily lives: how we clean our clothes, cool and heat our homes, light our spaces, run our various digital devices, and cook our food is (or has the potential to be) powered with electricity. Such everyday entanglements with electricity are becoming more visible through broader efforts to reduce the use of fossil fuels across the US. With the passage of the Bipartisan Infrastructure Lawl (BIL) in 2021 and the Inflation Reduction Act (IRA) in 2022, there has been a historic influx of federal funding into efforts to foster a “clean energy economy.” Within this broader investment, the Department of Energy’s (DOE) Weatherization Assistance Program (WAP) has received $3.5 billion dollars from BIL alone, with more funding expected to come from the IRA on top of the formula funds that are appropriated to the program by congress each year. Due to its work in clean energy and energy efficiency, WAP programs fall within the scope of the Biden Administration’s Justice40 initiative, in which all relevant programs must ensure that 40% of the overall benefits of federal investments flow to “disadvantaged communities” as defined by the Climate and Economic Justice Screening tool. My ethnographic research with the Colorado Energy Office’s Weatherization Assistance Program examines how WAP employees, as they seek to integrate Justice40 initiatives into the program, are expanding their understanding of beneficial electrification and energy efficiency measures as existing within a complex assemblage of human and non-human relationships, materialities, policies, and daily rhythms that represent “home.” Yet, the bureaucratic structures materializing around directing these resources risk (re)entrenching the inequities of the current fossil fuel(ed) era. In particular, I examine the challenges that have emerged from early efforts to calculate energy burden as a quantitative indicator of need in prioritizing electrification efforts.

The Weatherization Assistance Program is a product of the 1970s oil crisis, with a mission to save income-qualified residents money on their utility bills by offering quick and easy energy efficiency measures at no cost to residents. Since its creation in 1976, the program has grown in scope and technological complexity. Through partnerships with US national energy labs, WAP has developed its signature “house as a system” methodology in which a home’s building envelope, heating and cooling systems, electrical systems, and electric baseload appliances are understood as deeply interconnected in order to realize a home’s potential to be energy efficient, and more importantly, to ensure it is a safe and healthy space for those who live there. More recently, Colorado’s Weatherization Assistance Program’s whole-home approach  has experienced a major expansion as the program integrates decarbonization initiatives in the form of beneficial electrification measures (i.e. installing air-source heat pumps, electric water heaters, and solar) into residential single-family, multi-family, and mobile homes across the state.

 In a memo sent to WAP agencies last September, DOE “strongly recommend[ed]” considering energy burden as a criterion to prioritize which clients are served by WAP in one of its first steps in addressing Justice40 (DOE Memo 094). Energy burden is defined as the percentage of gross income spent on household energy costs annually, with a burden of 6% considered high and 10% and above considered extreme (DOE). To calculate energy burden, WAPs need to collect a resident’s income and the amount they pay for energy annually, via their utility bills. In the memo, DOE insists that energy burden provides a crucial indicator for which citizens are disproportionately impacted by energy prices, and collecting better energy burden data is imperative in directing resources to those most in need of them.

After receiving the memo, Colorado’s WAP started to receive incisive pushback from its network of agencies that implement energy efficiency and electrification measures on the ground. My research with agency staff revealed that agencies prioritize residents that are considered elderly, disabled, or have children under 5, but none of the agencies have a formal process for prioritizing clients that do not fit into these categories; up until a few years ago the program was so small the agencies didn’t feel the need to. Once it is determined that a client fits within the income requirements for the program, they are added to an agency’s waitlist and prioritized in a variety of informal ways. In Alamosa, a rural community located in Colorado’s San Luis Valley, an agency intake specialist told me that she tries her best to sit down with clients to review their application and their latest utility bill when they apply. From these conversations she can determine how urgently a client needs WAP services. “I am worried about using energy burden to know what someone needs over anyone else. I had a lady come in last month who was sealing off her children’s bedroom so that her space heaters could warm her living room without raising her bill too much. She wouldn’t show up with high energy burden because she was working so hard to lower her bill.” I heard similar stories and concerns across the agencies. In Arapahoe county, located just east of the city of Denver, a field technician told me about an elderly couple who refused to let him touch their thermostat when he showed up to their house. “They were dressed from head to toe in winter clothes, they even had gloves on so they wouldn’t need to turn up the heat.”

Quantitative tools have a long history in modern industrialized societies (Porter 1995; Hacking 1975; Desrosieres 2002) as mechanisms through which to categorize, rank, and compare “virtually any complex field of human affairs” (Rottenburg and Merry 2015: 12). As a quantitative indicator, energy burden represents one of the first building blocks in creating an audit culture (Strathern 2005) that attempts to track and shape the transition away from fossil fuels towards clean energy sources in ways that center justice.  While its simplistic nature allows DOE and the Colorado Energy Office to “govern at a distance” (Wright and Shore 2011: 3), ethnographic evidence suggests that it could solidify how agencies understand energy justice in ways that erase experiences, actions, and people. Energy burden, if left as a purely quantitative indicator, has the potential to become what Boyer (2019) terms an “energopolitical apparatus” due to its role of “reinforcing both the inertia of a particular organization of fuel and a particular organization of state-based political power” (16).

So the question becomes: if neoliberal economics has endorsed quantitative indicators as a means to produce a world that is knowable without the detailed particulars of context and history (Silverstein 2018), how can we move past such technologies of accountability to understand communities with the sociohistorical context needed to center energy and environmental justice in electrification efforts? In many ways, this is the goal of ethnographic knowledge. To shed light on the ways that energy use and energy practices are contingent on deeply social, historical, and political processes that involve complex assemblages of both human and nonhuman actors. Perhaps the equally challenging task in this historical moment is for anthropologists to apply this knowledge in actionable ways; to not only point to old mechanisms of accountability that risk (re)entrenching harmful and brittle categories, but to take a risk in shifting these epistemologies ourselves. 

References:

Boyer, Dominic. 2019. Energopolitics. Duke University Press.

Cool, Alison. 2019. “Impossible, Unknowable, Accountable: Dramas and Dilemmas of Data Law:” Social Studies of Science, May.

Desrosieres, A., 2002. The Politics of Large Numbers: A History of Statistical Reasoning. Harvard University Press.

Espeland, W.N., Sauder, M., 2007. Rankings and Reactivity: How Public Measures Recreate Social Worlds. American Journal of Sociology 113, 1–40.

Espeland, Wendy Nelson, and Mitchell L. Stevens. 1998. “Commensuration as a Social Process.” Annual Review of Sociology 24: 313–43.

Hacking, Ian. 1975. The Emergence of Probability: A Philosophical Study of Early Ideas about Probability, Induction and Statistical Inference. Cambridge ; New York: Cambridge University Press.

Irvine, Judith, and Susan Gal. 2000. “Language Ideology and Linguistic Differentiation.”

Merry, Sally Engle. 2011. “Measuring the World: Indicators, Human Rights, and Global Governance.” Current Anthropology 52 (S3): S83–95.

Mitchell, Timothy. 2009. “Carbon Democracy.” Economy and Society 38 (3): 399–432.

Nye, David. 1999. Consuming Power: A Social History of American Energies. The MIT Press.

Porter, Theodore M. 1995. Trust in Numbers. Princeton, N.J: Princeton University Press.

Rottenburg, R., Merry, S.E., Park, S.-J., Mugler, J., 2015. The world of indicators: The making of governmental knowledge through quantification. Cambridge University Press.

Shore, Cris, and Susan Wright. 2003. Anthropology of Policy: Perspectives on Governance and Power. Routledge.

Silverstein, Brian. 2018. “Commensuration, Performativity, and the Reform of Statistics in Turkey.” American Ethnologist 45 (3): 330–40.

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