Becoming Urban
Bibliographic record
Abstract
The transformations entangled in becoming an urban society are increasingly attracting attention in archaeology, including in the Mediterranean. The place-making entailed in the development of urban settlement represents a fundamental change for a society; it creates over time a new urban mentalité and habitus, such that the urban fabric and place become an active part of social life, and its reproduction. While urbanism does not require the ‘state’, urban settlements form key venues for social, economic and political change leading to the potential development of sedentary early complex polities. For several areas of the world and in multiple periods, there are increasingly sophisticated studies of urbanisation. To date, Cyprus has received relatively little attention—but, as increasingly recognised, urbanisation was central to the island’s rapid change into, and emergence as, a substantial element of the Late Bronze Age eastern Mediterranean world. We consider and critique the case of urbanisation on Late Bronze Age Cyprus and highlight its importance to Cypriot and eastern Mediterranean prehistory. We explore in detail one particular case, the Maroni valley area and its Late Bronze Age complex, where relatively detailed information is becoming available from a combination of excavations, pedestrian survey and archaeological geophysics. We argue that only such detailed study allows proper recognition of the nature and anatomy of urban settlements on prehistoric Cyprus; we also argue that the scale (spatial and demographic) of the main Late Bronze Age urban settlements on Cyprus should not be underestimated.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.034 | 0.006 |
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".