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Record W4225424094 · doi:10.24908/iqurcp15482

History of Archaeological Work and Attitudes Towards Antiquities at Uruk

2022· article· en· W4225424094 on OpenAlexvenueno aff
Tina Abo Al-Soof

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArchaeological Research and Protection
Canadian institutionsnot available
Fundersnot available
KeywordsExcavationArchaeologyPoliticsPeriod (music)HistoryArchitectureUrbanizationBeakerAncient cityAncient historyLawArtPolitical science

Abstract

fetched live from OpenAlex

Uruk, also known as Warka, is an ancient Mesopotamian site in modern Iraq that has been the focus of archaeological exploration for over 165 years. Excavations at Uruk have revealed cultural remains from the Eridu period (ca. 5000 BCE) until the Parthian and Sasanian periods (ca. first and second centuries CE). The site is a key point of reference for understanding the development of early urbanisation, writing, architecture, production, and social structure. Over 165 years, changing politics, methods of archaeology and attitudes towards antiquities have affected the way the site was handled. My project focuses on those critical changes which reveal the evolution of archaeology from a Western-dominated affair to a more inclusive practice. In this presentation, I will discuss and evaluate the history of archaeological work and attitudes towards antiquities at Uruk with an emphasis on the teams that excavated there, their methods of excavation, the conditions of the permits they were given, and significant finds and their subsequent distribution. The analysis will be divided into historical time periods (from the Ottoman Period to Iraq after the US-led invasion of 2003) based on the modern history of this region. Governmental and professional policies are also explored in regard to antiquities laws, methods of archaeology and local versus foreign involvement.

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)0.003
metaresearch head score (Gemma)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.210
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.004
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.144
GPT teacher head0.331
Teacher spread0.187 · 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 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

Citations0
Published2022
Admission routes1
Has abstractyes

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