Cities are different animals: A zooarchaeology of urbanism at Hamoukar, Syria, 5th–3rd millennia BC
Bibliographic record
Abstract
The advent of urbanism marks a significant shift in human lifeways, and comparative study has shown that the world has seen many different forms of urbanism. We argue that animals were a fundamental part of what made cities different from other forms of settlement and different from one another. In this article, we provide the first long-term, diachronic analysis of a Mesopotamian city that foregrounds the evolving role of animals. We argue that the site of Hamoukar in northeastern Syria is best viewed as a succession of three cities, each distinctive in its own way and each dependent on animals in its own fashion. To make this argument, we summarize urban dynamics at Hamoukar from the late 5th through mid-late 3rd millennia BC, with a particular focus on faunal remains. We show that intensive and potentially long-distance caprine management was key to the first city; a more mixed animal economy, with caprines potentially harvested for wool, defined the second city; and pigs dominated the meat supply of the third city. Analysis of changing patterns in species composition, caprine survivorship, secondary products exploitation, and biometrics demonstrates that the three different cities were––both literally and metaphorically––different animals. • Cities are multispecies spaces and centers animals in urban economy. • A diachronic zooarchaeological analysis from an early Mesopotamian city. • Analyses of species composition, caprine survivorship, and biometrics. • Changes in animal economy define Hamoukar as three successive cities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".