The paper “A return to function as the basis of lithic classification” by Radu Iovita (2024) is a contribution to an upcoming volume on the role of typology and type-thinking in current archaeological theory and praxis edited by the PCI recommenders. In this context, the paper offers an in-depth discussion of several crucial dimensions of typological thinking in past and current lithic studies, namely:

• “common sense” in archaeology, discussed based on earlier proposals by influential anthropologist Clifford Geertz (1975),
• “function”, argued by the author to be the “fundamental property of tools”,
• “cognitive” aspects, said to be reflected in the “property we naturally use to classify” stone tools and then argued to be grounded in function,
• “traceology” as an archaeological bundle of methods and practices to determine (tool) function, discussing the current status of this research perspective in archaeology and its future.

Discussing and importantly re-articulating these concepts, Iovita ultimately aims at “establishing unified guiding principles for studying a technology that spans several million years and several different species whose brain capacities range from ca. 300–1400 cm³”.

The notion that tool function should dictate classification is not new (e.g. Gebauer 1987). It is particularly noteworthy, however, that the paper engages carefully with various relevant contributions on the topic from non-Anglophone research traditions. First, its considering works on lithic typologies published in other languages, such as Russian (Sergei Semenov), French (Georges Laplace), and German (Joachim Hahn). Second, it takes up the ideas of two French techno-anthropologists, in particular: 

• Anthropologist of technics François Sigaut's (1940-2012) distinction of form, function, and “fonctionnement” (Sigaut 1991). Iovita proposes to draw and recast this tripartition, splitting the notion of function into “structural function” (a concept encompassing biological function as well as the “interface between the tool and its environment”), “operation” (which “relates to learning the function of artifacts from others and representing them through their motor associations”), and "designer-intended function” (DIF). Iovita shows how these distinctions can be used to clarify the ways and the grounds on which we build lithic typologies.
• Structural anthropologist Claude Lévi-Strauss' (1908-2009) concept of “bricolage”, influentially proposed and developed in his La pensée sauvage (Lévi-Strauss 1962); this concept was also much discussed by North American anthropologist Clifford Geertz and more recently critically re-considered in the English-speaking literature thanks to a new translation of Lévi-Strauss' original text (Lévi-Strauss 2021).

Interestingly, Iovita grounds his argumentation on insights from primatology, psychology and the cognitive sciences, to the extent that they fuel discussion on archaeological concepts and methods. Results regarding the so-called “design stance” for example play a crucial role: coined by philosopher and cognitive scientist and philosopher Daniel Dennett (1942-2024), this notion encompasses the possible discrepancies between the designer’s intended purpose and the object's current functions. DIF, as discussed by Iovita, directly relates to this idea, illustrating how concepts from other sciences can fruitfully be injected into archaeological thinking.

Lastly, readers should note the intellectual contents generated on PCI as part of the reviewing process of the paper itself: both the reviewers and the author have engaged in in-depth discussions on the idea of (tool) “function” and its contested relationship with form or typology, delineating and mapping different views on these key issues in lithic study which are worth reading on their own.

References

Gebauer, A. B. (1987). Stylistic Analysis. A Critical Review of Concepts, Models, and Interpretations, Journal of Danish Archaeology, 6, p. 223–229.

Geertz, C. (1975). Common Sense as a Cultural System, The Antioch Review, 33 (1), p. 5–26.

Iovita, R. (2024). A return to function as the basis of lithic classification. Zenodo, 7734147, ver. 5 peer-reviewed and recommended by Peer Community in Archaeology. https://doi.org/10.5281/zenodo.7734147

Lévi-Strauss, C. (1962). La pensée sauvage. Paris: Plon.

Lévi-Strauss, C. (2021). Wild Thought: A New Translation of “La Pensée sauvage”. Translated by Jeffrey Mehlman & John Leavitt. Chicago, Illinois: University of Chicago Press.

Sigaut, F. (1991). “Un couteau ne sert pas à couper, mais en coupant. Structure, fonctionnement et fonction dans l'analyse des objets” in 25 Ans d'études technologiques en préhistoire : Bilan et perspectives, Juan-les-Pins: Éditions de l'association pour la promotion et la diffusion des connaissances archéologiques, p. 21-34.

The paper “A closer look at an eroded dune landscape: first functional insights into the Federmessergruppen site of Lommel-Maatheide” [1] focuses on the final Palaeolithic (Federmesser) site of Lommel-Maatheide. Federmesser sites from northern Belgium such as Lommel-Maatheide, Meer and Rekem, show evidence for dense human occupation of specific areas located on top of Tardiglacial dunes nearby water bodies [2]. Preserved spatial distribution of finds at the sites suggest different activity areas and the presence of habitat structures [2]. However, because of the low organic preservation at the sites, functional analyses of lithic assemblages have the potential to significantly contribute to the spatial organisation of activities at these sites. This study by Tomasso et al. [1], represents an excellent example of a large-scale integrated approach to the study of lithic industries. The article undoubtedly demonstrates the potential of the proposed methodology and the reliability of the results obtained.

The article explores two different aspects (linked and excellently interconnected here): the possibility to apply use wear, residue and fracture analyses, on lithic assemblages affected by taphonomical alterations and to study lithic assemblages from dune landscapes. 

The study allows to answer differentiated questions: what is the influence of taphonomical alterations on use wear analysis? How do excavation methods impact the formation of use wear and the preservation of residues? Can we recognize distinct domestic activities? The article also provides an interesting hypothesis about hunting activities and propulsion methods.

The applied methodology is effectively interdisciplinary and innovative. It demonstrates how a truly integrated and articulated approach can represent the turning point for going beyond a mainly descriptive dimension to move towards a real understanding of the sites.

Studies dedicated to the analysis of the propulsion mode are not very frequent, but they are surely very important to better understand human behaviour [3]. Here, the methodology developed for the evaluation of the propulsion mode represent an important starting point for the definition of a new approach. Morphological and morphometrical analysis are integrated to the evaluation of the mechanical stress, to fracture delineations and to the hafting system (the latter defined on experimental basis).

This article therefore underlines the potential of combining different approaches to functional analysis associated with a ‘tailored’ reference collection and applying them to a high number of artefacts for reconstructing past human activities involving materials that are otherwise not preserved in these contexts. 

[1] Tomasso, S., Cnuts, D., Coppe, J., Geerts, F., Gils, M.V., Bie, M.D., Rots, V. (2021). A closer look at an eroded dune landscape: first functional insights into the Federmessergruppen site of Lommel-Maatheide. https://doi.org/10.31219/osf.io/pf3sm, ver 3 peer-reviewed and recommended by PCI Archaeology.

[2] De Bie, M., Van Gils, M. (2006). Les habitats des groupes à Federmesser (aziliens) dans le Nord de la Belgique. Bulletin de la Société préhistorique française, 103, 781–790.

[3] Coppe, J., Lepers, C., Clarenne, V., Delaunois, E., Pirlot, M. and Rots V. (2019). Ballistic Study Tackles Kinetic Energy Values of Palaeolithic Weaponry. Archaeometry, (61)4, 933-956. https://doi.org/10.1111/arcm.12452

The paper entitled “Investigating relationships between technological variability and ecology in the Middle Gravettian (ca. 32-28 ky cal. BP) in France” [1] submitted by A. Vignoles and colleagues offers a robust and interesting new analysis of the niche differences between the Rayssian and Noaillian facies of the Middle Gravettian in France.

Understanding technological variability in the Palaeolithic is a long-standing challenge. Previous debates have vacillated between strong, quasi-ethnic culture-historical interpretations rooted in the traditional European school and extreme functional stances that would see artefact forms and their frequencies with assemblages conditioned by site function. While both positions have their merits, many empirical and conceptual caveats haunt them equally [see 2]. In this new study Vignoles and colleagues, so-called eco-cultural niche modelling is applied in an attempt to explore whether, and if so, which environmental background factors may have conditioned the emergence and persistence of two sub-cultural categories (facies) within the Middle Gravettian: the Rayssian and the Noaillian. These are are defined through, respectively, a specific knapping method and the presence of a specific burin type, and the occurrence of these seems divided by the Garonne River. Eco-cultural niche modelling has emerged as an archaeological application of distribution models widely employed in ecology, including palaeoecology, to understand organismal niche envelopes [3]. They constitute powerful tools for using the spatial and chronological information inherent in the archaeological record to up-scale interpretations of human-environment relations beyond individual site stratigraphies or dating series. Another important feature of such models is that their performance can, as Vignoles et al. also show, be formally evaluated and replicated. Following on from earlier applications of such techniques [e.g. 4], the authors here present an interesting study that uses very specific archaeological indicators – namely the Raysse method and the Noaillian burin – as defining features for the units (communities, traditions) whose adaptations they investigate. While broad tool types have previously been used as cultural taxonomic indicators in niche modelling studies [5], the present study is ambitious in its attempt to understand variability at a relatively small spatial scale. This mirrors equally interesting attempts of doing so in later prehistoric contexts [6].

Applications of niche modelling that use analytical units defined through archaeological characteristics (technology, typology) are opening up exciting new opportunities for pinning down precisely which environmental or climatic features these cultural components reference, if any. The study by Vignoles et al. makes a good case. At the same time, this approach also acutely raises questions of cultural taxonomy, of how we define our units of analysis and what they might mean [7]. It remains unclear to whether we can define such units on the basis of very different technological traits if the aim is to then use them as taxonomically equivalent in subsequent analyses. There is also a risk that these facies become reified as traditions of sub-cultures – then often further equated with specific people – through an overly normative view of their constituent technological elements. In addition, studies of adaptation in principle need to be conscious of the so-called ‘Galton’s Problem’, where the historical relatedness of the analytical units in question need to be taken into account in seeking salient correlations between cultural and environmental features [8]. In pushing forward eco-cultural niche modelling, the study by Vignoles et al. thus takes us some way forward in understanding the potentially adaptive variability within the Gravettian; future work should consider more strongly the specific historical relatedness amongst the cultural taxa under study and follow more theory-driven definition thereof. Such definition would also allow the post-analysis interpretations of eco-cultural niche modelling to be more explicit. Without doubt, the Gravettian as a whole – including, for instance, phenomena such as the Maisierian [9] – would benefit from additional and extended applications of this method. Similarly, other periods of the Palaeolithic also characterized by such variability (e.g. the Magdalenian and Final Palaeolithic) offer additional cases moving forward.

Bibliography

[1] Vignoles, A. et al. (2020). Investigating relationships between technological variability and ecology in 1 the Middle Gravettian (ca. 32-28 ky cal. BP) in France. PCI Archaeology. 10.31219/osf.io/ud3hj

[2] Dibble, H.L., Holdaway, S.J., Lin, S.C., Braun, D.R., Douglass, M.J., Iovita, R., McPherron, S.P., Olszewski, D.I., Sandgathe, D., 2017. Major Fallacies Surrounding Stone Artifacts and Assemblages. Journal of Archaeological Method and Theory 24, 813–851. 10.1007/s10816-016-9297-8

[3] Svenning, J.-C., Fløjgaard, C., Marske, K.A., Nógues-Bravo, D., Normand, S., 2011. Applications of species distribution modeling to paleobiology. Quaternary Science Reviews 30, 2930–2947. 10.1016/j.quascirev.2011.06.012

[4] Banks, W.E., d’Errico, F., Dibble, H.L., Krishtalka, L., West, D., Olszewski, D.I., Townsend Petersen, A., Anderson, D.G., Gillam, J.C., Montet-White, A., Crucifix, M., Marean, C.W., Sánchez-Goñi, M.F., Wolfarth, B., Vanhaeren, M., 2006. Eco-Cultural Niche Modeling: New Tools for Reconstructing the Geography and Ecology of Past Human Populations. PaleoAnthropology 2006, 68–83.

[5] Banks, W.E., Zilhão, J., d’Errico, F., Kageyama, M., Sima, A., Ronchitelli, A., 2009. Investigating links between ecology and bifacial tool types in Western Europe during the Last Glacial Maximum. Journal of Archaeological Science 36, 2853–2867. 10.1016/j.jas.2009.09.014

[6] Whitford, B.R., 2019. Characterizing the cultural evolutionary process from eco-cultural niche models: niche construction during the Neolithic of the Struma River Valley (c. 6200–4900 BC). Archaeological and Anthropological Sciences 11, 2181–2200. 10.1007/s12520-018-0667-x

[7] Reynolds, N., Riede, F., 2019. House of cards: cultural taxonomy and the study of the European Upper Palaeolithic. Antiquity 93, 1350–1358. 10.15184/aqy.2019.49

[8] Mace, R., Pagel, M.D., 1994. The Comparative Method in Anthropology. Current Anthropology 35, 549–564. 10.1086/204317

[9] Pesesse, D., 2017. Is it still appropriate to talk about the Gravettian? Data from lithic industries in Western Europe. Quartär 64, 107–128. 10.7485/QU64_5

In a recent article, Fumihiro Sakahira and Hiro'omi Tsumura (2023) used social network analysis methods to analyze change in obsidian trade networks in Japan throughout the 13,000-year-long Jomon period. In the paper recommended here (Sakahira and Tsumura 2024), Social Network Analysis of Ancient Japanese Obsidian Artifacts Reflecting Sampling Bias Reduction they revisit that data and describe additional analyses that confirm the robustness of their social network analysis. The data, analysis methods, and substantive conclusions of the two papers overlap; what this new paper adds is a detailed examination of the data and methods, including use of bootstrap analysis to demonstrate the reasonableness of the methods they used to group sites into clusters.

Both papers begin with a large dataset of approximately 21,000 artifacts from more than 250 sites dating to various times throughout the Jomon period. The number of sites and artifacts, varying sample sizes from the sites, as well as the length of the Jomon period, make interpretation of the data challenging. To help make the data easier to interpret and reduce problems with small sample sizes from some sites, the authors assign each site to one of five sub-periods, then define spatial clusters of sites within each period using the DBSCAN algorithm. Sites with at least three other sites within 10 km are joined into clusters, while sites that lack enough close neighbors are left as isolates. Clusters or isolated sites with sample sizes smaller than 30 were dropped, and the remaining sites and clusters became the nodes in the networks formed for each period, using cosine similarities of obsidian assemblages to define the strength of ties between clusters and sites.

The main substantive result of Sakahira and Tsumura’s analysis is the demonstration that, during the Middle Jomon period (5500-4500 cal BP), clusters and isolated sites were much more connected than before or after that period. This is largely due to extensive distribution of obsidian from the Kozu-shima source, located on a small island off the Japanese mainland. Before the Middle Jomon period, Kozu-shima obsidian was mostly found at sites near the coast, but during the Middle Jomon, a trade network developed that took Kozu-shima obsidian far inland. This ended after the Middle Jomon period, and obsidian networks were less densely connected in the late and last Jomon periods.

The methods and conclusions are all previously published (Sakahira and Tsumura 2023). What Sakahira and Tsumura add in Social Network Analysis of Ancient Japanese Obsidian Artifacts Reflecting Sampling Bias Reduction are:

·       an examination of the distribution of cosine similarities between their clusters for each period

·       a similar evaluation of the cosine similarities within each cluster (and among the unclustered sites) for each period

·       bootstrap analyses of the mean cosine similarities and network densities for each time period

These additional analyses demonstrate that the methods used to cluster sites are reasonable, and that the use of spatially defined clusters as nodes (rather than the individual sites within the clusters) works well as a way of reducing bias from small, unrepresentative samples. An alternative way to reduce that bias would be to simply drop small assemblages, but that would mean ignoring data that could usefully contribute to the analysis.

The cosine similarities between clusters show patterns that make sense given the results of the network analysis. The Middle Jomon period has, on average, the highest cosine similarities between clusters, and most cluster pairs have high cosine similarities, consistent with the densely connected, spatially expansive network from that time period. A few cluster pairs in the Middle Jomon have low similarities, apparently representing comparisons including one of the few nodes on the margins on the network that had little or no obsidian from the Kozu-shima source. The other four time periods all show lower average inter-cluster similarities and many cluster pairs have either high or low similarities. This probably reflects the tendency for nearby clusters to have very similar obsidian assemblages to each other and for geographically distant clusters to have dissimilar obsidian assemblages. The pattern is consistent with the less densely connected networks and regionalization shown in the network graphs. Thinking about this pattern makes me want to see a plot of the geographic distances between the clusters against the cosine similarities. There must be a very strong correlation, but it would be interesting to know whether there are any cluster pairs with similarities that deviate markedly from what would be predicted by their geographic separation.

The similarities within clusters are also interesting. For each time period, almost every cluster has a higher average (mean and median) within-cluster similarity than the similarity for unclustered sites, with only two exceptions. This is partial validation of the method used for creating the spatial clusters; sites within the clusters are at least more similar to each other than unclustered sites are, suggesting that grouping them this way was reasonable.

Although Sakahira and Tsumura say little about it, most clusters show quite a wide range of similarities between the site pairs they contain; average within-cluster similarities are relatively high, but many pairs of sites in most clusters appear to have low similarities (the individual values are not reported, but the pattern is clear in boxplots for the first four periods). There may be value in further exploring the occurrence of low site-to-site similarities within clusters. How often are they caused by small sample sizes? Clusters are retained in the analysis if they have a total of at least 30 artifacts, but clusters may contain sites with even smaller sample sizes, and small samples likely account for many of the low similarity values between sites in the same cluster. But is distance between sites in a cluster also a factor? If the most distant sites within a spatially extensive cluster are dissimilar, subdividing the cluster would likely improve the results. Further exploration of these within-cluster site-to-site similarity values might be worth doing, perhaps by plotting the similarities against the size of the smallest sample included in the comparison, as well as by plotting the cosine similarity against the distance between sites. Any low similarity values not attributable to small sample sizes or geographic distance would surely be worth investigating further.

Sakahira and Tsumura also use a bootstrap analysis to simulate, for each time period, mean cosine similarities between clusters and between site pairs without clustering. They also simulate the network density for each time period before and after clustering. These analyses show that, almost always, mean simulated cosine similarities and mean simulated network density are higher after clustering than before. The simulated mean values also match the actual mean values better after clustering than before. This improved match to actual values when the sites are clustered for the bootstrap reinforces the argument that clustering the sites for the network analysis was a reasonable result.

The strength of this paper is that Sakahira and Tsumura return to reevaluate their previously published work, which demonstrated strong patterns through time in the nature and extent of Jomon obsidian trade networks. In the current paper they present further analyses demonstrating that several of their methodological decisions were reasonable and their results are robust. The specific clusters formed with the DBSCAN algorithm may or may not be optimal (which would be unreasonable to expect), but the authors present analyses showing that using spatial clusters does improve their network analysis. Clustering reduces problems with small sample sizes from individual sites and simplifies the network graphs by reducing the number of nodes, which makes the results easier to interpret.

Reference

Sakahira, F. and Tsumura, H. (2023). Tipping Points of Ancient Japanese Jomon Trade Networks from Social Network Analyses of Obsidian Artifacts. Frontiers in Physics 10:1015870. https://doi.org/10.3389/fphy.2022.1015870

Sakahira, F. and Tsumura, H. (2024). Social Network Analysis of Ancient Japanese Obsidian Artifacts Reflecting Sampling Bias Reduction, Zenodo, 10057602, ver. 7 peer-reviewed and recommended by Peer Community in Archaeology. https://doi.org/10.5281/zenodo.7969330

Even though applications of 3D recording have existed in archaeology for a long time, it is only since the early 2000s that this field of research has become mainstream thanks to technological advances, and the availability of low-cost sensors and image-based modelling software. This has led to significant changes in the way archaeological sites are documented. This paper entitled "Understanding Archaeological Site Topography: 3D Archaeology of Archaeology" by Jitte Waagen & Gert Jan van Wijngaarden (2024) presents an overview of the current developments in the application possibilities of 3D site topography recording in archaeology. The paper is the result of the round table discussion "Understanding Archaeological Site Topography: 3D Archaeology of Archaeology" at the CAA conference on 5 April 2023 in Amsterdam, with contributions from Radu Brunchi, Nicola Lercari, Joep Orbons, Davide Tanasi, Alicia Walsh, Pawel Wolf and Teagan Zoldoske.

The paper starts with a discussion of the Amsterdam Troy Project (ATP). In the frame of the ATP, the rich history of archaeological activity (over 150 years of fieldwork) at Troy is being studied to explore how previous archaeological research has helped to shape the current topography of the site and how these earlier research activities, embedded in their contemporary theoretical frameworks, have determined our understanding of the site (see Murray and M. Spriggs 2017, Carver 2011 for the influence of theory on archaeological fieldwork and archaeology as a discipline), the so-called 'Archaeology of Archaeology' approach. In addition to studying previous research records and re-excavating old excavation trenches, a central element of the project is the 3D recording of the past and present topography of the site in order to reconstruct the archaeological research activities at the site and their impact on the archaeological landscape.

The paper focuses on current trends in 3D recording of archaeological site topography and discusses three main areas where 3D recording of archaeological site topography can contribute to the "Archaeology of Archaeology" approach: (1) monitoring the topography of sites for preservation, conservation, research and dissemination purposes; (2) reconstructing, reevaluating and reinterpreting past archaeological research efforts; and (3) archiving in a 4D (GIS) environment. This is done using the example of the Amsterdam Troy project and comparing it with other projects using similar methods and approaches. Using these case studies, the authors effectively discuss the impact of these technologies on the understanding of the topography of archaeological sites and how 3D recording can enhance archaeological research methodologies and interpretations, for example, by not using such 3D approaches as a stand-alone product but integrating them with available information from previous research activities. They also recognise the limitations and challenges involved, such as the need for customised data acquisition strategies and the lack of ready-made software solutions for developing comprehensive data management strategies.

One topic that could have been covered in more detail is how 3D site topography recording (and 3D recording in general) is affected by current theoretical developments in archaeology. Like any other archaeological fieldwork or data collection approach, it is a child of its time. Decisions such as what to record, how to record, what to store, how to store, what to visualise, and how to visualise influence our understanding of archaeological sites (Ward 2022). This minor critical reflection aside, the paper makes a timely and significant contribution to archaeology by addressing current trends and the limitations of the increasingly widespread use of 3D site topography recording technologies.

References

Carver, G. (2011). Reflections on the archaeology of archaeological excavation, Archaeological Dialogues 18(1), pp. 18–26. https://doi.org/10.1017/S1380203811000067

Murray, T. and Spriggs, M. (2017). The historiography of archaeology: exploring theory, contingency and rationality, World Archaeology 49(2), pp. 151–157. https://doi.org/10.1080/00438243.2017.1334583

Ward, C. (2022). Excavating the Archive / Archiving the Excavation: Archival Processes and Contexts in Archaeology, Advances in Archaeological Practice 10(2), pp. 160–176. https://doi.org/10.1017/aap.2022.1

Waagen, J. and van Wijngaarden, G.J. (2024). Understanding Archaeological Site Topography: 3D Archaeology of Archaeology, Zenodo, 10061343, ver. 3 peer-reviewed and recommonded by Peer Community in Archaeology. https://doi.org/10.5281/zenodo.10061343