Constructing Empowerment through Interpretations of Environmental Surveillance Data

Abstract

Environmental surveillance data-in particular, data from air monitoring conducted by grassroots community groups-is presumed to empower community members with respect to neighboring industrial facilities; furthermore, extensions of datacollecting ability are assumed to represent expansions of empowerment. This paper challenges the idea that empowerment follows from the collection of copious surveillance data, arguing instead that the degree and kind of empowerment environmental surveillance supports is determined by the manner in which surveillance data is made meaningful. Examining contrasting interpretations of environmental surveillance data, the paper shows how they variously construct empowerment in terms of the power to define issues, the power to enforce laws, and the power to choose. The three forms of empowerment vary in the level at which they enable community groups to act-suggesting that the empowering potential of surveillance rests in large part on strategic interpretive choices.

The Domestication of Data: Why Embracing Digital Data Means Embracing Bigger Questions

“…While there is not yet available research on how people use such devices in their homes, there are precedents in environmental activism where "ordinary" people take samples of the air and have them analyzed in a lab in order to make claims about pollution in their communities. This research shows that people who live in areas strongly affected by pollution can and do develop notions about what the data is telling them (Ottinger 2010). In areas with large oil refineries, for example, Ottinger reports that it is not difficult to find people with fairly well defined beliefs about the inadequacy of year-long or twenty four hour averages as a way of processing pollutant data.…”

“…We can also see in each domain different levels of interest in gate-keeping from expert communities of practice. In the air quality example, citizens' claims about proper data processing are hugely contested by other actors with whom civic groups have conflicts (Ottinger 2010). These contests play out in decidedly "mixed methods" territory.…”

Practicing environmental data justice: From DataRescue to Data Together

“…They have also produced alternative forms of environmental data, since most information about pollution in the US is industry self‐reported or reliant on inadequate or incomplete collection methods (Agyeman et al., ; Altman et al., ; Brown, ; Corburn, ; Ottinger, ; Saxton, ; Shapiro et al., ). As one example, in the 1990s, organisers from a neighbourhood on the border of a Shell chemical facility in Louisiana developed a low‐cost method of air quality monitoring, called “air buckets.” They did so because they discovered that the state – which had declared Shell Chemical's air quality emissions “safe”– was relying on inadequate data on the air they breathed (Allen, ; Lerner, ; Ottinger, ). The state was collecting data on the average of toxic chemicals over long 24‐hour periods, and comparing these to ambient air standards.…”

Environmental Research Translation: Enhancing interactions with communities at contaminated sites

“…For example, Ottinger (2010) demonstrates STS in practice, where she conducted an ethnographic research study in three Louisiana communities where community members employed air monitoring instruments to measure hazards stemming from their proximity to one or more major petrochemical facilities (Ottinger, 2010). By observing the relationship between the environmental surveillance data collected and community empowerment, Ottinger (2010) concluded “that the empowering potential of surveillance data rests in large part on strategic interpretive choices”. Ottinger and Cohen (2011) edited a compilation of case studies, discussing how the environmental justice movement has begun to transform science and engineering practices.…”