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Record W2069075538 · doi:10.1086/506288

Biological and Ethnic Identity in New Kingdom Nubia

2006· article· en· W2069075538 on OpenAlexaff
Michele R. Buzon

Bibliographic record

VenueCurrent Anthropology · 2006
Typearticle
Languageen
FieldArts and Humanities
TopicForensic Anthropology and Bioarchaeology Studies
Canadian institutionsUniversity of Alberta
FundersUniversity of CambridgeNational Science Foundation
KeywordsEthnic groupKingdomAgency (philosophy)Context (archaeology)Power (physics)Identity (music)EthnologyAnthropologyPopulationEthnically diverseGeographyHistoryGenealogyArchaeologyAncient historySociologyDemographyArtAestheticsBiologySocial science

Abstract

fetched live from OpenAlex

Past studies of culture contact have often used the concepts of unidirectional modification of a subordinate population by a socially dominant group. Reevaluations of these ideas suggest that this paradigm is not appropriate for all situations. The examination of power relations in such alternative circumstances provides insights into human agency, as it highlights the dynamic, bidirectional interactions that can occur between two cultures. The relationship between the peoples of ancient Nubia and Egypt provides an excellent opportunity to study alternative power relations in a welldocumented cultural context. During the New Kingdom period (ca. 15501050 BC), Egypt succeeded in occupying most of Nubia. At the site of Tombos, located in northern Sudan, Egyptianization of Nubians makes it impossible to judge from textual and archaeological evidence who ruled Nubia: Egyptian colonists or Nubian leaders. Analysis of cranial measurements of individuals from Tombos and other comparable sites, in conjunction with archaeological indications of ethnicity, suggests that Tombos was inhabited by an ethnically and biologically mixed group of people who used ethnic symbols in advantageous ways.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.540
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.036
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.124
GPT teacher head0.369
Teacher spread0.245 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
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

Citations52
Published2006
Admission routes1
Has abstractyes

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