Cited by 199Archaeological Research and ProtectionArchaeology and Cultural HeritageArchaeological and Geological Studies

The DOI matches its Crossref record; 233 of the 241 references it cites were found in a registry or an index; 5 of the 70 sources its claims cite were checked for support.

Integrating Archaeological Theory and Predictive Modeling: a Live Report from the Scene

Open access
Verhagen, Philip, Whitley, Thomas G.·2012·Journal of Archaeological Method and Theory

Abstract

Archaeological predictive modeling has been used successfully for over 20 years as a decision-making tool in cultural resources management. Its appreciation in academic circles however has been mixed because of its perceived theoretical poverty. In this paper, we discuss the issue of integrating current archaeological theoretical approaches and predictive modeling. We suggest a methodology for doing so based on cognitive archaeology, middle range theory, and paleoeconomic modeling. We also discuss the problems associated with testing predictive models.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

The paper argues that archaeological predictive modeling has been theoretically impoverished and proposes integrating cognitive archaeology, middle range theory, and paleoeconomic modeling to build explanatory, testable models. It illustrates this with the Georgia Coast caloric-return model and discusses persistent problems of testing, observational bias, scale, and predicting unusual sites.

Key findings

  • The authors propose a cognitive predictive modeling approach in which decisions bridge observed conditions and past events, using cost-benefit and caloric-return logic; the Georgia Coast model uses 37 forage categories, 12 months, 444 GIS surfaces at 30 m resolution over 4,669,484 acres, yielding 20,996,530 map units.
  • In a 36 by 28 km Georgia/Florida sample with 308 sites, splitting composite caloric returns into low, moderate, and high categories produced a Kvamme’s gain statistic in excess of 0.80, whereas the best correlative or intuitive models did not produce gains better than 0.57; almost all sites in low-potential areas were along edges of high or moderate probability areas.
  • For Late Bronze Age/Early Iron Age urnfields in the southern Netherlands, the authors assess Roymans and Kortlang’s theory against Binford’s middle-range criteria and find it only partly fulfills them; they suggest testing alternative models of fission/colonization versus intensification, with territory estimates such as ca. 300 ha per urnfield and communities of three to six families (20–40 people).
  • They conclude that inductive/correlative methods remain useful for exploratory data analysis and gap-filling, while explanatory cognitive models can serve as heuristic and predictive tools; controlled field tests of predictive models are still very rare.

Methods

  • Conceptual and theoretical synthesis: the paper reviews the history of archaeological predictive modeling, processual/post-processual debates, middle range theory, cognitive archaeology, and agent-based/complexity approaches, then proposes a methodology.
  • Case illustration: the Georgia Coast Lower Coastal Plain paleoeconomic model consists of a Habitat Model, Available Caloric Model, and Returned Caloric Model, using environmental attractors, forage categories, monthly caloric returns, and cost-distance foot/canoe travel; a 36 by 28 km sample with 308 sites is used to test a composite caloric-return surface via Kvamme’s gain statistic.
  • Secondary case: the southern Netherlands urnfield/celtic field settlement debate is used to examine how archaeological theory can be translated into middle range theory for predictive modeling; the authors state that a predictive model for this case is still lacking.

Limitations

  • Stated: controlled field tests of predictive models are still very rare; the Georgia Coast model cannot be used directly for behaviors not related to daily subsistence activities, such as burials, because benefits are not easily quantified or spatialized; issues remain with group agency, temporality, predicting unusual occurrences, and scale/resolution.
  • Stated: observational bias from non-probabilistic survey and CRM-driven survey threatens model development and testing; the uniformitarian condition is problematic for explaining social change; there is no universal method for integrating all archaeological theory into predictive modeling.
  • Evident from the text: the Georgia Coast model is described as “still a work in progress” and has not yet been applied to the entire study area; the southern Netherlands example is illustrative only and lacks an operational predictive model; dynamical modeling tools remain technically difficult and not off-the-shelf.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1007/s10816-011-9102-7

Cites

233 of 233 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Figures

Fig. 1 The procedure used for inductive predictive modeling. A statistical comparison of archaeological data and ' environmental ' variables is used to create a predictive model. This model is then tested either through statistical methods using withheld or new data or by means of peer review (expert judgment). After Kamermans and Wansleeben (1999)
Fig. 1 The procedure used for inductive predictive modeling. A statistical comparison of archaeological data and ' environmental ' variables is used to create a predictive model. This model is then tested either through statistical methods using withheld or new data or by means of peer review (expert judgment). After Kamermans and Wansleeben (1999)CC-BY-NC · From the PDF
Image 2
CC-BY-NC · From the PDF
Fig. 2 The procedure used for deductive predictive modeling. The model is created on the basis of hypotheses on site location preferences. In many cases, these are no more than ' educated guesses. ' The model can easily be tested with statistical methods as the archaeological data set is not used for building the model. After Kamermans and Wansleeben (1999)
Fig. 2 The procedure used for deductive predictive modeling. The model is created on the basis of hypotheses on site location preferences. In many cases, these are no more than ' educated guesses. ' The model can easily be tested with statistical methods as the archaeological data set is not used for building the model. After Kamermans and Wansleeben (1999)CC-BY-NC · From the PDF
Fig. 3 The position of modeling in the scientific research process. Quantitative methods and models can play a role in almost any stage of scientific research but are best applied in the stages where theory is developed and made suitable for testing. The separation between hypothesis and theory however may not always be as clear as suggested. Adapted after O ' Sullivan and Gahegan (2007)
Fig. 3 The position of modeling in the scientific research process. Quantitative methods and models can play a role in almost any stage of scientific research but are best applied in the stages where theory is developed and made suitable for testing. The separation between hypothesis and theory however may not always be as clear as suggested. Adapted after O ' Sullivan and Gahegan (2007)CC-BY-NC · From the PDF
Image 5
CC-BY-NC · From the PDF
Fig. 5 Location of the Georgia Coast study area
Fig. 5 Location of the Georgia Coast study areaCC-BY-NC · From the PDF
Image 7
CC-BY-NC · From the PDF
Image 8
CC-BY-NC · From the PDF
Image 9
CC-BY-NC · From the PDF
Image 10
CC-BY-NC · From the PDF
Fig. 10 Illustration of other potential interpretative surfaces resulting from the modeling
Fig. 10 Illustration of other potential interpretative surfaces resulting from the modelingCC-BY-NC · From the PDF

Verification

Claims the paper makes

152 Own interpretation · 41 No basis given · 18 Sources not found · 15 No full text of the sources · 7 Not checked yet · 3 Couldn’t confirm · 2 Partly supported · 1 Own method · 1 Own result · accuracy not yet measured

Show all 61 claims

  • It may state two separate claims as one. 68
  • Probably not a substantial claim. 148
  • The quote only partly states this claim. 4
179 of 179
  • The paper relies on this without support.

    The location of human settlement is closely related to characteristics of the natural environment.

    “But the realization that the location of human settlement is closely related to characteristics of the natural environment, coupled with the processual emphasis on quantitative methods, was what enabled the formulation of statistical models for the prediction of site density in areas where no archaeological sites had yet been found.”
  • The authors state this as an assumption.

    Prehistoric farmers would have preferred fertile land for agriculture.

    “For example, the assumption that prehistoric farmers would have preferred fertile land for agriculture is hardly contentious.”
  • The authors state this as an assumption.

    Certain soil types are more productive than others and therefore supported more settlements.

    “theory readily gives way to the basic practical notion that certain soil types are more productive than others and therefore the corresponding units depicted on the soil map will have supported more settlements.”
  • The paper relies on this without support.

    A predictive model based on the various theoretical approaches suggested is still lacking.

    “For the moment, however, a predictive model based on the various theoretical approaches suggested is still lacking, and the example is only used here to illustrate the complexities of translating various theoretical approaches into middle range theory that could be used for predictive modeling purposes.”
  • The authors state this as an assumption.

    A steadily rising population occurred during the whole Late Bronze Age/Early Iron Age period in the southern Netherlands.

    “On the basis of the number of known burial sites, a steadily rising population is assumed during the whole period (see also Gerritsen 2003; this assumption is however challenged by Fokkens 2002, pp. 143-144).”
  • The authors state this as an assumption.

    A threefold increase in population occurred at the beginning of the Early Iron Age compared to the Middle Bronze Age.

    “Compared to the Middle Bronze Age, a threefold increase in population is postulated at the beginning of the Early Iron Age.”
  • The authors state this as an assumption.

    The filling up of the landscape occurred by fission of small groups of people from existing settlements.

    “A process of”
  • The authors state this as an assumption.

    There is a causal link between population pressure and changes in agricultural production regime.

    “In general, a causal link is assumed between population pressure and changes in agricultural production regime.”
  • The authors state this as an assumption.

    The first settlements were installed before the urnfields.

    “It seems logical to assume that the first settlements were installed before the urnfields, so if we can get a grip on settlement location factors then we will have a good idea of potential urnfield locations as well.”
  • The paper relies on this without support.

    The processes involved in archaeological site formation are inherently inaccessible.

    “An important reason for early postprocessualists to reject Binford's concept of middle range theory (Hodder 1991) is the fact that the processes involved in archaeological site formation are inherently inaccessible.”
  • The authors state this as an assumption.

    Climatic conditions similar to today and a stable (modern) sea level since 4500 BP.

    “assuming climatic conditions similar to today and a stable (modern) sea level since 4500 BP.”
  • The authors state this as an assumption.

    Maintenance and collection costs decrease over time (between 4500 and 300 BP), while hunting success and harvest rates, as well as storage potentials, increase with certain specific technological changes.

    “The model assumes that maintenance (e.g., tool manufacture, making nets and weirs, habitat improvements, etc.) and collection costs (e.g., search times, setting and checking traps, etc.) decrease over time (between 4500 and 300 BP-the applicable time frame), while hunting success and harvest rates, as well as storage potentials, increase with certain specific technological changes (e.g.,”
  • The authors state this as an assumption.

    Energy conservation is a primary motivating factor for certain human spatial behaviors.

    “The only general rule or assumption required by the Georgia Coast Model is that of energy conservation as a primary motivating factor for certain human spatial behaviors.”
  • The authors state this as an assumption.

    The weapon deposition locations may have had regional or even supra-regional significance as places where competition between local groups could be played out.

    “They are never found outside fluvial contexts, and given the scarcity of these remains it is assumed that these locations may have had regional or even supra-regional significance as places where competition between local groups could be”
  • The paper relies on this without support.

    A certain amount of universality of individual actions is a necessary precondition for predictive modeling.

    “For predictive modeling, however, a certain amount of universality of individual actions is a necessary precondition, and it begs the question whether the appropriate unit of analysis is the individual or rather a larger social group.”
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Citations

Cites

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Metadata

Authors
Verhagen, P., & Whitley, T. G.
Affiliations
Vrije Universiteit Amsterdam (NL)
Corresponding author
Verhagen, Philip
Venue
Journal of Archaeological Method and Theory
Published
2011-02-01
Volume
19
Issue
1
Pages
49-100
ISSN
  • 1072-5369 (ISSN-L)
  • 1573-7764
OpenAlex
W2068976599
Cited by
190
References
241
Citations by year
2026: 20 · 2025: 11 · 2024: 7 · 2023: 21 · 2022: 16 · 2021: 13 · 2020: 14 · 2019: 18 · 2018: 12 · 2017: 13 · 2016: 13 · 2015: 11 · 2014: 9 · 2013: 5 · 2012: 7
FWCI
17.52
Type
journal article
Language
en
Open access
Licence
cc-by-nc
Locations
  • Journal of Archaeological Method and Theory (publishedVersion, cc-by-nc)
  • VU Research Portal (publishedVersion, other-oa)
  • UWA Profiles and Research Repository (UWA) (submittedVersion, other-oa)
  • Digital Academic REpository of VU University Amsterdam (Vrije Universiteit Amsterdam) (submittedVersion)
  • Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
Funders
  • National Science Foundation (0816400)
  • Colorado State University
  • Vrije Universiteit Amsterdam
  • Nederlandse Organisatie voor Wetenschappelijk Onderzoek
  • U.S. Geological Survey
Topics
  • Social Sciences › Archeology › Archaeological Research and Protection
  • Social Sciences › Arts and Humanities › Archeology (arts and humanities) › Archaeology and Cultural Heritage
  • Social Sciences › Arts and Humanities › Archeology (arts and humanities) › Archaeological and Geological Studies
Keywords
archaeological predictive modeling, archaeological theory, cognitive archaeology, middle-range theory, model testing, cultural resource management, decision-making

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