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Record W4403217095 · doi:10.1080/0067270x.2024.2411138

Making connections: ostrich eggshell beads as indicators of precolonial societal interaction in southeastern southern Africa

2024· article· en· W4403217095 on OpenAlexafffund
Peter Mitchell, Brian A. Stewart, Courtneay Hopper, Genevieve Dewar, Michael A. Schillaci

Bibliographic record

VenueAzania Archaeological Research in Africa · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicArchaeology and Rock Art Studies
Canadian institutionsThe Scarborough HospitalUniversity of TorontoUniversity of British Columbia
FundersUniversity of Toronto
KeywordsArchaeologyGeographyEggshellLater Stone AgeZooarchaeologyAncient historyEcologyHistoryBiology

Abstract

fetched live from OpenAlex

Ostriches are peculiar birds and their strangeness has been recognised by southern African hunter-gatherers through multiple symbolic associations. Such qualities are likely to have been enhanced where people had access to beads made from their eggshell but did not have direct knowledge of the birds themselves. Southeastern southern Africa, encompassing the Maloti-Drakensberg Mountains, the eastern half of the Eastern Cape Province and much of KwaZulu-Natal is one such area. We review the unusual attributes and associations of ostriches and their eggshell before briefly summarising previous work that has used strontium isotope analysis to investigate past bead exchange networks in this region. Because bead size can be controlled and patently varies through time and space, we then employ it as another potential indicator of the existence and spatial extent of past social networks. Having critically considered previous efforts in this field, we report on our work to build the largest sample of such data yet obtained in southern Africa and compare our preliminary results with other signals of interaction between precolonial hunter-gatherer and (where applicable) agropastoralist communities.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.426
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0020.003
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.159
GPT teacher head0.444
Teacher spread0.285 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2024
Admission routes2
Has abstractyes

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Same venueAzania Archaeological Research in AfricaSame topicArchaeology and Rock Art StudiesFrench-language works237,207