Systems theory, computer simulations and archaeology

Doran, Jim

doi:10.1080/00438243.1970.9979448

Cited by 28 publications

(15 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Well in line with the wider intellectual ethos of their time, foundational texts of what came to be known as processual archaeology are dominated by one of the various versions of system theory (e.g. Doran 1970, Salmon 1978. This trend is most noticeable in David Clarke's contribution with his conceptualisation of several specialised sub-systems all locked in many interaction and feedback loops (Clarke, 1968).…”

Section: Supporting the Holistic Hope Of Archaeologymentioning

confidence: 99%

“…As a result, and perhaps more so than any other social sciences, most archaeologists -explicitly or not -seem to subscribe to a Zeitgeist dominated by the idea that their discipline's goal is to explore the complexity of cultural and social human life in its entirety while at the same time avoiding the meta-synthesis "original sin", more or less the same positioning as anthropologists for present-time social science.Well in line with the wider intellectual ethos of their time, foundational texts of what came to be known as processual archaeology are dominated by one of the various versions of system theory (e.g. Doran 1970, Salmon 1978. This trend is most noticeable in David Clarke's contribution with his conceptualisation of several specialised sub-systems all locked in many interaction and feedback loops (Clarke, 1968).…”

mentioning

confidence: 99%

See 1 more Smart Citation

Trowels, Processors and Misunderstandings: Concluding Thoughts

Saqalli¹,

Linden²

2019

Integrating Qualitative and Social Science Factors in Archaeological Modelling

View full text Add to dashboard Cite

This conclusive text deals with the challenges of interdisciplinarity: Although conceptual and formal thresholds are well known within the scientific community, one may encounter difficulties for answering such related requirements: among them, the tension between the inherent holistic pretence of modelling and datarelated prosaicism is important as well as the simple fact that things, practices, assumptions and words are not the same among disciplines inducing unsolved misconceptions, misunderstandings and social bias. Also, seeking legitimacy and validity but also efficiency at the modelling project level, implying simplifications, interpolations an generalizations, is often in contradiction with the need for legitimacy at the level of each discipline involved. This is due of course to potentially contradictory scientific requirements of both levels and for a weight at least equivalent to the perfectly normal social need for recognition of each researcher, usually within its own discipline, to compare with the risky "business" in terms of reputation, results' over-expectation and time consumption of modelling approaches.Research community; social constraints to interdisciplinarity; go-and-return between fields and models; Supporting the holistic hope of ArchaeologyArchaeology, under its many theoretical variants, had always had a complex relationship with its selfacknowledged role as the gatekeeper of the past intricacy of all facets of human life over the very longue durée. Having to deal with a record first and foremost characterised by his patchiness and unevenness is to some extent counter-balanced by extraordinary access to an exciting diversity of sources, reflected by the countless methodological and technical refinements of the last few decades. We know that our window unto the past will always remain clouded in much haze, but we are constantly nudging it a bit more open. As a result, and perhaps more so than any other social sciences, most archaeologists -explicitly or not -seem to subscribe to a Zeitgeist dominated by the idea that their discipline's goal is to explore the complexity of cultural and social human life in its entirety while at the same time avoiding the meta-synthesis "original sin", more or less the same positioning as anthropologists for present-time social science.Well in line with the wider intellectual ethos of their time, foundational texts of what came to be known as processual archaeology are dominated by one of the various versions of system theory (e.g. Doran 1970, Salmon 1978. This trend is most noticeable in David Clarke's contribution with his conceptualisation of several specialised sub-systems all locked in many interaction and feedback loops (Clarke, 1968).

show abstract

Section: Supporting the Holistic Hope Of Archaeologymentioning

confidence: 99%

mentioning

confidence: 99%

Trowels, Processors and Misunderstandings: Concluding Thoughts

Saqalli¹,

Linden²

2019

Integrating Qualitative and Social Science Factors in Archaeological Modelling

View full text Add to dashboard Cite

show abstract

“…Examples of simulation methods in archaeology are unfortunately limited but are of great interest: Doran (1970), Thomas (1972), Ammermann and Cavalli-Sforza (1973), Wobst (1974), Zubrow (1975), Hassan (1977), Jochim (1976), Hodder ed. (1978, Renfrew and Cooke (1979), Sabloff (1981), Keene (1979), Belovsky (1987), Doran (1990), etc.…”

Section: Artefacts and Anthropological Modelsmentioning

confidence: 99%

Artefact analysis

2018

Clifton Quarry, Worcestershire

View full text Add to dashboard Cite

Historically, artefact analysis has focused on classifications and typologies. In fact, the typological approach may be considered as a particular cognitive step in the evolution of Archaeology. In this text more ambitious actual approaches of artefact analysis are described, relying on obtaining more cognitive information from artefacts. The applicable quantitative methods, which have been developed and tested to solve classical and modern archaeological problems, are detailed. Finally, a general methodology, founded on recent results in semiology, mathematical modelling and neuroscience, may be considered as a contribution to a renewed role of artefact analysis in archaeological reasoning. Perhaps our proposition is just a formalisation of evidence or common sense which archaeologists know well. But unfortunately, the history of archaeology provides us with thousands of examples of deceptive appearance of artefacts such as natural origin, geological alteration, manufacturing waste, random association with other artefacts, misinterpreted spatial structure, etc. History of artefacts in archaeology is also the history of diagnostic errors. With a methodological perspective, artefact analysis is a fundamental method in archaeology, with special needs to refer to semiology, taxonomy, systemic analysis, and finally cognitive science. At any level of archaeological reconstitution, artefact analysis is directly connected with the question of artefact knowledge. 3. A brief history of the concept of the artefact The history of the concept of the artefact in archaeology is strongly associated with the history of theoretical approaches in archaeology since the very beginning of this science. At first artefacts were merely "unknown things" and for that reason, they were collected and stored worldwide in "curiosity cabinets" of the upper classes.

show abstract

“…Although simulation techniques have been applied in archaeological research since the early days of the method (e.g., Doran 1970;Thomas 1973;Wobst 1974), they have not occupied such a central position in archaeology as they have done in other branches of science. The reasons behind this slow Pre-print version.…”

Section: Figure 1 the Relationship Between Data Analysis Tools And Smentioning

confidence: 99%

So You Think You Can Model? A Guide to Building and Evaluating Archaeological Simulation Models of Dispersals

Romanowska¹

2015

Human Biology

View full text Add to dashboard Cite

With the current surge of simulation studies in archaeology there is a growing concern for the lack of engagement and feedback between modellers and domain specialists. To facilitate this dialogue I present a compact guide to the simulation modelling process applied to a common research topic and the focus of this special issue of Human Biology-human dispersals. The process of developing a simulation is divided into nine steps grouped in three phases. ThePre-print version. Visit digitalcommons.wayne.edu/humbiol after publication for the final version.conceptual phase consists of identifying research questions (step 1) and finding the most suitable method (step 2), designing the general framework and the resolution of the simulation (step 3) and then by filling in that framework with the modelled entities and the rules of interactions (step 4). This is followed by the technical phase of coding and testing (step 5), parameterising the simulation (step 6) and running it (step 7). In the final phase the results of the simulation are analysed and re-contextualised (step 8) and the findings of the model are disseminated in publications and code repositories (step 9). Each step will be defined and characterised and then illustrated with examples of published human dispersals simulation studies. While not aiming to be a comprehensive textbookstyle guide to simulation, this overview of the process of modelling human dispersals should arm any non-modeller with enough understanding to evaluate the quality, strengths and weaknesses of any particular archaeological simulation and provide a starting point for further exploration of this common scientific tool.All archaeologists start modelling the moment they step out of the excavation trench. We interpret the individual finds (e.g., pots, skeletons, buildings etc.) within certain frameworks (e.g., pottery typologies, bone taxonomies, architectural types etc.) and analyse sets of finds to detect population level patterns (e.g., cultural similarities, age profiles of bone assemblages, urbanPre-print version. Visit digitalcommons.wayne.edu/humbiol after publication for the final version. development, etc.) with strict analytical rigour. However, the interpretations of these patterns in terms of human behaviour and causality are predominantly built using natural language, i.e. they are constructed in the form of conceptual models that hypothesise which causal mechanisms might have led from actions of individual actors (the owners of pots, users of skeletons and inhabitants of buildings) to the detected population-level patterns. These causal relationships are often described as, for example, "culture A influenced culture B," "the dispersal reached area C," or "population D outcompeted population E." Although inferences like these are made on the basis of rigorously collected and analysed data, and are commonly built upon extensive research and a good understanding of multiple strands of evidence, they nevertheless represent a thought experiment and are therefore limited ...

show abstract

Systems theory, computer simulations and archaeology

Cited by 28 publications

References 6 publications

Trowels, Processors and Misunderstandings: Concluding Thoughts

Trowels, Processors and Misunderstandings: Concluding Thoughts

Artefact analysis

So You Think You Can Model? A Guide to Building and Evaluating Archaeological Simulation Models of Dispersals

Contact Info

Product

Resources

About