Bibliographic record
Abstract
After an introductory section that frames some conceptual issues surrounding the emergence of city-states, most of the chapter is devoted to a chronological narrative describing the case of southern Mesopotamia. This includes sections on the pre-’Ubaid period, the ’Ubaid period, the Uruk period, and the post-Uruk period. The key puzzle is how to explain the transition from scattered villages and small towns in the ’Ubaid period to large city-states with tens of thousands of residents in the Uruk period. Following the main narrative, we review causal hypotheses on this subject proposed by archaeologists and economists. These include ideas about climate change, migration, food production, manufacturing, trade, warfare, and culture. We also offer a synthesis of our own. In our view, the prime mover was increasing aridity, which motivated migration from outlying areas toward the south. As this process unfolded, commoner living standards fell, which enabled local elites in the south to employ commoners at a lower wage. When the wage had fallen far enough, urban manufacturing became profitable. Elite taxation of urban manufacturing was probably easier than taxation of rural agriculture, and this provided the fiscal foundations for early city-states like Uruk.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".