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" Building A Baseline: Unifying Spatial and Temporal Methodologies to Understand Archaeological Looting in Egypt "
Fabiani, Michelle Rose Dippolito
Dugan, Laura
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Latin Dissertation
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English
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| Record Number
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1051675
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| Doc. No
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TL50792
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| Main Entry
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Fabiani, Michelle Rose Dippolito
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| Title & Author
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Building A Baseline: Unifying Spatial and Temporal Methodologies to Understand Archaeological Looting in Egypt\ Fabiani, Michelle Rose DippolitoDugan, Laura
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| College
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University of Maryland, College Park
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| Date
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2019
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| Degree
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Ph.D.
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2019
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| Note
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294 p.
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| Abstract
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Archaeological looting – the illegal excavation or removal of an antiquity from the ground or structural complex of an archaeological site – is a persistent issue in many countries. National and international laws, agreements, conventions, and statutes all proscribe the looting transporting, possession, and sale of antiquities illegally removed from archaeological sites. Looting has also generated a lot of academic attention, with scholarship developing in archaeology, sociology, criminology, and law (among others). Despite such legal proscriptions and scholarly contributions to understanding this phenomenon, current efforts have been unable to produce tangible solutions for preventing this crime. Not only has there not yet been extensive scholarship to understand the link between looting and contextual forces, there is a dearth of research on the most effective ways to study these interconnected variables. Using a framework of routine activity theory, this dissertation proposes a new possible approach that considers spatial, temporal, and spatio-temporal relationships to establish baseline data on patterns of archaeological looting attempts in Lower Egypt from 2015 to 2017 relative to sociopolitical, economic, and environmental stress — and to begin to address this research gap. Specifically, this dissertation proposes a methodology for collecting and coding data on archaeological looting attempts from satellite imagery. It then applies a series of spatial (clustering, proximity), temporal (SEM, VAR, ARDL), and spatio-temporal methods (clustering, hot spots analysis, spatial time series) to these data to demonstrate the importance of analyzing this phenomena multidimensionally.
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| Descriptor
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Archaeology
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Criminology
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Dugan, Laura
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University of Maryland, College Park
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