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Record W4311079165 · doi:10.15184/aqy.2022.141

The Jarigole mortuary tradition reconsidered

2022· article· en· W4311079165 on OpenAlexafffund
Elizabeth Sawchuk, Elisabeth Hildebrand, Austin Hill, Daniel A. Contreras, Justus Erus Edung, Anneke Janzen, Abdikadir Kurewa, James K. Munene, Emmanuel Ndiema, Katherine M. Grillo

Bibliographic record

VenueAntiquity · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicRangeland Management and Livestock Ecology
Canadian institutionsUniversity of Alberta
FundersNational Commission for Science, Technology and InnovationNational Geographic SocietySocial Sciences and Humanities Research Council of CanadaWenner-Gren Foundation
KeywordsMegalithPillarPastoralismExcavationArchaeologyPeriod (music)GeographyHistoryAncient historyLivestockArtEngineeringForestry

Abstract

fetched live from OpenAlex

The megalithic pillar sites found around Lake Turkana, Kenya, are monumental cemeteries built approximately 5000 years ago. Their construction coincides with the spread of pastoralism into the region during a period of profound climate change. Early work at the Jarigole pillar site suggested that these places were secondary burial grounds. Subsequent excavations at other pillar sites, however, have revealed planned mortuary cavities for predominantly primary burials, challenging the idea that all pillar sites belonged to a single ‘Jarigole mortuary tradition’. Here, the authors report new findings from the Jarigole site that resolve long-standing questions about eastern Africa's earliest monuments and provide insight into the social lives, and deaths, of the region's first pastoralists.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0060.021
Scholarly communication0.0050.004
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.012
GPT teacher head0.212
Teacher spread0.199 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations7
Published2022
Admission routes2
Has abstractyes

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