This Grammar Walkthrough is part of the online grammar textbook Analyzing Grammar in Context - https://faculty.unlv.edu/nagelhout/AnalyzingGrammarInContext/index.html
ABSTRACT
The study of the Roman economy is populated by a large number ofsometimes conflicting descriptive models. These models are rarelyformally compared, and many remain untested due to the limited use offormal hypothesis testing methods in Roman studies and the significantdata requirements to enable their use. This paper illustrates how broadpatterns in large archaeological datasets allow for aspects of thesemodels to be tested, and suggests agent-based network modelling as aparticularly fruitful approach for the study of the Roman economy.
As an example, this paper presents the Market Economy and Roman CeramicsRedistribution agent-based network model (MERCURY, after the Roman godof commerce). It represents the structure of social networks betweentraders that act as the channels for the flow of commercial informationand goods. MERCURY was created to formally represent and compare twodescriptive models of the functioning of the Roman trade system (PeterBang's Roman bazaar (2008) and Peter Temin's (2013) Roman marketeconomy) and how these give rise to differences in the distributionpatterns of Roman tablewares. The results of experiments using MERCURYare subsequently compared to archaeologically observed tablewaredistribution patterns. The results suggest that, contrary to Bang'shypothesis, limited availability of reliable commercial information fromdifferent markets is unlikely to give rise to the large differences inthe wideness of tableware distributions observed in the archaeologicalrecord. This paper concludes that the study of the Roman economy wouldvery much benefit from embracing computational modelling approachesbecause (i) it forces scholars to consider the comparability ofdescriptive models, (ii) it allows comparison of simulated outputs witharchaeologically observed outputs, and (iii) it allows to map out thegrey zone between extreme hypotheses and refocus our descriptive modelsaway from hypotheses that do not compare favourably with thearchaeological record.
http://hdl.handle.net/11858/00-1780-0000-0024-5022-5
This Grammar Walkthrough is part of the online grammar textbook Analyzing Grammar in Context - https://faculty.unlv.edu/nagelhout/AnalyzingGrammarInContext/index.html
ABSTRACT
The study of the Roman economy is populated by a large number ofsometimes conflicting descriptive models. These models are rarelyformally compared, and many remain untested due to the limited use offormal hypothesis testing methods in Roman studies and the significantdata requirements to enable their use. This paper illustrates how broadpatterns in large archaeological datasets allow for aspects of thesemodels to be tested, and suggests agent-based network modelling as aparticularly fruitful approach for the study of the Roman economy.
As an example, this paper presents the Market Economy and Roman CeramicsRedistribution agent-based network model (MERCURY, after the Roman godof commerce). It represents the structure of social networks betweentraders that act as the channels for the flow of commercial informationand goods. MERCURY was created to formally represent and compare twodescriptive models of the functioning of the Roman trade system (PeterBang's Roman bazaar (2008) and Peter Temin's (2013) Roman marketeconomy) and how these give rise to differences in the distributionpatterns of Roman tablewares. The results of experiments using MERCURYare subsequently compared to archaeologically observed tablewaredistribution patterns. The results suggest that, contrary to Bang'shypothesis, limited availability of reliable commercial information fromdifferent markets is unlikely to give rise to the large differences inthe wideness of tableware distributions observed in the archaeologicalrecord. This paper concludes that the study of the Roman economy wouldvery much benefit from embracing computational modelling approachesbecause (i) it forces scholars to consider the comparability ofdescriptive models, (ii) it allows comparison of simulated outputs witharchaeologically observed outputs, and (iii) it allows to map out thegrey zone between extreme hypotheses and refocus our descriptive modelsaway from hypotheses that do not compare favourably with thearchaeological record.
http://hdl.handle.net/11858/00-1780-0000-0024-5022-5