Modeling the Mojave: Old Data, New Futures, and the Semiotics of Empty Space
Author(s): Alaina Wibberly
Year: 2021
Summary
This is an abstract from the "SAA 2021: General Sessions" session, at the 86th annual meeting of the Society for American Archaeology.
The settler colonial history of the Mojave Desert may be defined less by its expansion and more by its various failures and withdrawals. Drawing on a dataset of historic refuse sites that spans two centuries and three million acres, this paper uses spatial modeling to map the landscape’s trajectory toward waste-land. The trash dumps and mining ruins that dominate the material record testify to cycles of extraction, exhaustion, and abandonment as settlers struggled to find value in the United States' driest desert. These colonial histories preface an equally colonial present in which the value of the Mojave lies in its value-lessness: hazardous waste dumping, extractive industry, and military test ranges put the desert’s “empty space” to use. Might the archaeological record be used to challenge the inevitability of such a future, which threatens both Indigenous sovereignty and the landscape’s ecological survival? Statistical modeling, as a tool that embraces linear progress, can be applied critically to the progress-oriented history of colonial expansion as a representational method whose slippages reveal alternate futures. Embracing GIS modeling as speculative archaeology, this paper attempts to unwind the trajectory of settler logic and challenge the myth of “empty space” in the colonial encounter.
Cite this Record
Modeling the Mojave: Old Data, New Futures, and the Semiotics of Empty Space. Alaina Wibberly. Presented at The 86th Annual Meeting of the Society for American Archaeology. 2021 ( tDAR id: 467652)
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Keywords
General
Colonialism
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Digital Archaeology: GIS
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Historic
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Landscape semiotics
Geographic Keywords
North America: California and Great Basin
Spatial Coverage
min long: -124.189; min lat: 31.803 ; max long: -105.469; max lat: 43.58 ;
Record Identifiers
Abstract Id(s): 33139