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P. Jeffrey Brantingham

Researcher at University of California, Los Angeles

Publications -  96
Citations -  4989

P. Jeffrey Brantingham is an academic researcher from University of California, Los Angeles. The author has contributed to research in topics: Plateau & Population. The author has an hindex of 36, co-authored 95 publications receiving 4307 citations. Previous affiliations of P. Jeffrey Brantingham include University of California & Santa Fe Institute.

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Correcting temporal frequency distributions for taphonomic bias

TL;DR: Surovell et al. as discussed by the authors developed an empirical model of taphonomic bias, which is the tendency for younger things to be overrepresented relative to older things in the archaeological record due to the operation of destructive processes like erosion and weathering.
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Impact of social distancing during COVID-19 pandemic on crime in Los Angeles and Indianapolis.

TL;DR: Examination of the most recently available data from both Los Angeles, CA, and Indianapolis, IN, shows that social distancing has had a statistically significant impact on a few specific crime types, however, the overall effect is notably less than might be expected given the scale of the disruption to social and economic life.
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A Neutral Model of Stone Raw Material Procurement

TL;DR: A behaviorally neutral agent-based model is developed involving a forager engaged in a random walk within a uniform environment that acknowledges the possibility that Paleolithic behavioral adaptations were sometimes not responsive to differences between stone raw material types in the ways implied by current archaeological theory.
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A note on the use of temporal frequency distributions in studies of prehistoric demography

TL;DR: This paper showed that the typical positive curvilinear frequency distributions observed in archaeological contexts also regularly occur in paleontological and geological contexts and are thus likely caused by the operation of time-dependent destructive processes, what they call "taphonomic bias".
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Dissipation and displacement of hotspots in reaction-diffusion models of crime

TL;DR: In this article, the authors present a mathematical framework based on reaction-diffusion partial differential equations for studying the dynamics of crime hotspots, which is based on empirical evidence for how offenders move and mix with potential victims or targets.