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Record W4409695600 · doi:10.1080/00934690.2025.2483615

Greasing the Wheels of Urbanism: Innovating Early Bronze Age Olive Oil Production in the Northern Jordan Valley

2025· article· en· W4409695600 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Field Archaeology · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicArchaeology and Historical Studies
Canadian institutionsUniversity of Toronto
FundersUniversity of Toronto
KeywordsBronze AgeUrbanismArchaeologyAncient historyOlive oilGeographyBronzeHistoryEconomyArchitectureEconomics

Abstract

fetched live from OpenAlex

Initial phases of urbanization are messy, with innovations leading to successes and failures. How people changed their resource production strategies to meet developing needs during urbanizing periods is a foundational aspect of understanding the emergence of early cities. This article focuses on Site WZ130, a late 4th millennium b.c. olive-processing site in northern Jordan that was active during the Early Bronze Age (EBA, 3800–2000 b.c.), when the first urban societies emerged in the southern Levant. Site WZ130 provides a tangible example of the infrastructural innovations that were necessary to support early urbanism. The site’s three phases demonstrate successive innovation in olive-pressing technology, from layering pulp in a pit, a technique used since the Neolithic, to beam pressing, which survived into the 20th century a.d. These changes in olive-processing methods demonstrate that people responded to socio-economic and political changes brought on by early urbanization through innovation and experimentation in olive oil production.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.535
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.242
Teacher spread0.217 · 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