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Department of Archaeology

 
Read more at: ArchBiMod – Agent-Based Modelling to assess the quality and bias of the archaeological record

ArchBiMod – Agent-Based Modelling to assess the quality and bias of the archaeological record

Archaeological data is often biased and incomplete. This is a well-known issue for most archaeologists. Although studies of specific sites and small regions can have this into account, the effect of this problem increases exponentially as archaeologists expand their chronological and geographic frame, and try to answer questions related to general dynamics and broad human processes.


Read more at: B-CARED

B-CARED

The bioarchaeological characterization of disabled individuals from the past is particularly challenging because it pushes the boundaries of the interpretation of pathologies recognisable on human remains. With my project, namely B-CARED, I will investigate the bioarchaeological approaches for recreating “Past to life”. In so doing, the osteobiographical approach offers a possible framework, in which human remains are used to understand not only the embodied experience during life but also seeing people as playing diverse social roles (e.g.


Read more at: EHSCAN-Exploring Early Holocene Saharan Cultural Adaptation and Social Networks through socio-ecological inferential modelling

EHSCAN-Exploring Early Holocene Saharan Cultural Adaptation and Social Networks through socio-ecological inferential modelling

EHSCAN is a Horizon-MSCA-2022-PF scheme Fellowship Funded by UKRI and hosted by the McDonald Institute for Archaeological Research, University of Cambridge. 


Read more at: ENCOUNTER

ENCOUNTER

ENCOUNTER investigates the Jomon-Yayoi transition, a demic and cultural diffusion event that led the predominantly hunting, gathering, and fishing-based communities of the Japanese islands to adopt rice and millet farming during the 1st millennium BC.


Read more at: REVERSEACTION: Reverse engineering collective action: complex technologies in stateless societies

REVERSEACTION: Reverse engineering collective action: complex technologies in stateless societies

Cooperation is a markedly human mix of innate and learned behaviour, and a key to tackling some of our greatest concerns. Paradoxically, studies of social dynamics often focus on hierarchies, state formation and political structures ruled by coercive power, with comparatively little regard to the mechanisms whereby humans voluntarily collaborate. Encouragingly, new research on collective action is reconciling classic anthropology with game theory and empirical studies of group resource management, thus heralding a fundamental transformation.


Read more at: Transitions in early stone tool technologies: a computer vision and machine learning approach

Transitions in early stone tool technologies: a computer vision and machine learning approach

The transition from Oldowan to Acheulean technologies are hypothesised to be concomitant with advances in cognition and behaviour. However, the nature of these shifts, and their cultural and evolutionary implications are poorly defined and understood. While extensive literature exists on these technologies, significant differences in research methods and traditions make comparative and comprehensive analyses problematic.