A large trolling lure shank from Ahuahu Great Mercury Island, New Zealand

Furey, Louise; Phillipps, Rebecca; Emmitt, Joshua; McAllister, Andrew; Holdaway, Simon

doi:10.15286/jps.129.1.85-112

Cited by 5 publications

(10 citation statements)

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“…Furey and colleagues (2020) provide details of a trolling lure shank made from serpentinite found at Waitapu. It is unusual in its large size and completeness, the largest example retrieved from an archaeological site in Aotearoa.…”

Section: Descriptions and Contradictionsmentioning

confidence: 99%

“…A notched pendant made from petrified wood, perforated shark teeth, an imitation whale tooth pendant and shaped cylinders of ochre ( kokowai ) were also recovered. The importance placed on these objects comes partly from aesthetics, but also from ethnohistoric accounts and contemporary heritage values (Furey et al 2020). For the most part, however, their archaeological value derives from assumptions about curation.…”

Section: Descriptions and Contradictionsmentioning

confidence: 99%

“…papers in Anderson & Smith 1996; Furey 2002; Furey et al . 2020). In contrast, most discussions of flaked stone material see these as debitage, the residue from the production of intended end products.…”

Section: Introductionmentioning

confidence: 99%

“…As well, there were blocks of prepared kokowai (red ochre). Bones thought of as faunal material included numerous dog bones and fragments of whale bone (Furey et al 2020). Two concentrations of artefacts are identifiable stratigraphically, with most of the artefacts associated with lower layers and dated by radiocarbon to the fourteenth century.…”

Section: Introductionmentioning

confidence: 99%

“…At both sites, obsidian artefacts together with those made from other materials, occur together with well-designed and manufactured artefacts, and some forms that represented high, yet unrealized, raw material potential. Some artefacts are truly exceptional, interpreted as ornaments with high symbolic significance (Furey 2002; Furey et al 2020). In both sites, artefacts occur in sand deposits subject to erosion and redeposition without definitive evidence for structures that might explain the association of the mundane with the exceptional (grave goods, for example).…”

Section: Introductionmentioning

confidence: 99%

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Artefact Categories, Artefact Assemblages and Ontological Alterity

Holdaway

Phillipps

2020

CAJ

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Joan Gero argued that archaeological interpretation is not the accumulation of truth but rather an ideological construct. Post-colonial studies building on Gero's work critique notions of universal value, that aspects of human cultural heritage hold value for all peoples. However, these studies are not specific about what a post-colonial analysis of the archaeological record might look like, particularly involving material culture categories. What appear as fundamental artefact classes remain and so appeal to a form of universal value. Here we employ a novel application of the ontological turn, specifically Holbraad's method of ontography, to break away from conventional approaches to stone artefact categorization and interpretation. We use Lucas’ discussion of materialization to develop an alternative approach to artefact categories considering two assemblages of artefacts from the North Island of Aotearoa. Both feature large numbers of obsidian artefacts. The obsidian provides the means to investigate levels of historical use, since the material is identifiable to geological source, analysable technologically and retains traces of use. Using the results of obsidian analyses, we investigate the concepts on which archaeologists have based assessments of the relationships among material culture items, suggesting ways in which archaeologists might consider creating space for post-colonial ontologies.

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Section: Descriptions and Contradictionsmentioning

confidence: 99%

Section: Descriptions and Contradictionsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Artefact Categories, Artefact Assemblages and Ontological Alterity

Holdaway

Phillipps

2020

CAJ

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Machine learning for stone artifact identification: Distinguishing worked stone artifacts from natural clasts using deep neural networks

et al. 2022

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Stone artifacts are often the most abundant class of objects found in archaeological sites but their consistent identification is limited by the number of experienced analysts available. We report a machine learning based technology for stone artifact identification as part of a solution to the lack of such experts directed at distinguishing worked stone objects from naturally occurring lithic clasts. Three case study locations from Egypt, Australia, and New Zealand provide a data set of 6769 2D images, 3868 flaked artifact and 2901 rock images used to train and test a machine learning model based on an openly available PyTorch implementation of Faster R-CNN ResNet 50. Results indicate 100% agreement between the model and original human derived classifications, a better performance than the results achieved independently by two human analysts who reassessed the 2D images available to the machine learning model. Machine learning neural networks provide the potential to consistently assess the composition of large archaeological assemblages composed of objects modified in a variety of ways.

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A Comparison of Volumetric Reconstruction Methods of Archaeological Deposits Using Point-Cloud Data from Ahuahu, Aotearoa New Zealand

et al. 2021

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Collection of 3D data in archaeology is a long-standing practice. Traditionally, the focus of these data has been visualization as opposed to analysis. Three-dimensional data are often recorded during archaeological excavations, with the provenience of deposits, features, and artefacts documented by a variety of methods. Simple analysis of 3D data includes calculating the volumes of bound entities, such as deposits and features, and determining the spatial relationships of artifacts within these. The construction of these volumes presents challenges that originate in computer-aided design (CAD) but have implications for how data are used in archaeological analysis. We evaluate 3D construction processes using data from Waitetoke, Ahuahu Great Mercury Island, Aotearoa, New Zealand. Point clouds created with data collected by total station, photogrammetry, and terrestrial LiDAR using simultaneous localization and mapping (SLAM) are compared, as well as different methods for generating surface area and volumes with triangulated meshes and convex hulls. The differences between methods are evaluated and assessed in relation to analyzing artifact densities within deposits. While each method of 3D data acquisition and modeling has advantages in terms of accuracy and precision, other factors such as data collection and processing times must be considered when deciding on the most suitable.

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A large trolling lure shank from Ahuahu Great Mercury Island, New Zealand

Cited by 5 publications

References 0 publications

Artefact Categories, Artefact Assemblages and Ontological Alterity

Artefact Categories, Artefact Assemblages and Ontological Alterity

Machine learning for stone artifact identification: Distinguishing worked stone artifacts from natural clasts using deep neural networks

A Comparison of Volumetric Reconstruction Methods of Archaeological Deposits Using Point-Cloud Data from Ahuahu, Aotearoa New Zealand

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