'The tool didn't make decisions for us': metrics and the performance of accountability in environmental governance.

Governments use metrics made possible by new data technologies to allocate budgets, manage pandemics, valorize ecosystems, and demonstrate how these actions are legitimate. Big data is pointed to as providing objective answers that emerge untampered from observations of the world as it is – a view from nowhere. While data is more valued than ever in environmental governance, so too are arrangements that seek stakeholders' input and otherwise address their subjective interests – a view from everywhere. Different kinds of metrics perform state actors as accountable in both registers: metrics that are responsive to dynamic conditions; that account for specific stakeholders; that can be prioritized against one another in interactive data visualization tools. Louisiana, USA's Coastal Master Plan is an attempt to stem wetlands loss through fine-scale modeling of large volumes of data and calculation of these kinds of social and environmental metrics. State actors there make accountability claims that appear contradictory: their decisions are legitimate because they are driven by the best available coastal science and technology, while their data tools 'didn't make decisions for us.' As state actors deploy environmental big data and metrics to make sense of it, we should be able to explain these apparently contradictory stances and the controversies that result. STS theory on metrics in environmental governance benefits from characterizing how 'modes of authorized seeing' are given expression by different metrical forms and what brings modes into contact and conflict. [ABSTRACT FROM AUTHOR]