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Record W3016422567 · doi:10.1017/lis.2020.3

Ordering the land beyond the Sixth Cataract: Imperial policy, archaeology and the role of Henry Wellcome

2020· article· en· W3016422567 on OpenAlexaff
Isabelle Vella Gregory

Bibliographic record

VenueLibyan Studies · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArchaeological Research and Protection
Canadian institutionsArthur B. McDonald-Canadian Astroparticle Physics Research Institute
FundersSociety for Libyan StudiesWellcome Trust
KeywordsContext (archaeology)ArchaeologyPoliticsHistoryNarrativePost-medieval archaeologyExcavationAncient historyGeographyArtLawPolitical science

Abstract

fetched live from OpenAlex

Abstract The Sudan occupies a fairly complex place in archaeological enquiry. This is not a result of the archaeological record, rather it is due to a particular perception of the Sudan, its archaeology and history. The first excavators were archaeologists and anatomists who either worked in Egypt or in the Mediterranean, while the Anglo-Egyptian Condominium encouraged white-only scholars to both conduct research and to be active members of the newly formed political service in order to ‘know the natives’. In other words, archaeology from the outset was intimately connected to a particular political narrative and aim. This paper traces the historical context from the early 20th century to the development of archaeology south of beyond the Sixth Cataract south of the present-day capital of Khartoum, showing how it was created by Henry Wellcome. In particular, it focuses on the vast mortuary and habitation site of Jebel Moya, south-central Sudan, where new fieldwork is yielding fruitful results. Henry Wellcome's contribution to archaeology remains under-acknowledged. This long-overdue critical assessment traces and contextualizes the historical trajectories at play and situates them within the broader historical archaeology context.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.016
Scholarly communication0.0060.002
Open science0.0000.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.025
GPT teacher head0.258
Teacher spread0.233 · 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 designNot applicable
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

Citations46
Published2020
Admission routes1
Has abstractyes

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