Were Cities Built as Images?
Bibliographic record
Abstract
Many ancient city sites display a remarkable regularity in their plan which has led to considerable debate on the symbolism and intentionality which may lie behind these arrangements. Grid plan cities of the Greek and Roman world were discussed by Haverfield almost a century ago, but it was above all the cities of South and East Asia analyzed by Wheatley in his influential Pivot of the Four Quarters (1971) which has given new emphasis to the potential of meaning and significance. Such planned cities necessarily incorporate an essential tension between praxis — the practical day-to-day needs of the urban community — and idealism, the desire to impose on those practical concerns a city-plan which expresses a symbolic or cosmological image. Contemporary texts, where they exist, may help towards an answer, but the physicality of the city plan itself provides the crucial ground for argument as to whether symbolic or ideological imperatives governed the actual outcome. Cities may be conceptualized in ideal terms without ever taking on the physical attributes of any ideal form. The contributors to this Viewpoint approach the issue from a diversity of standpoints and with reference to different geographical areas. Were cities built as images? Did powerful belief systems combined with strong centralized control give rise to cities where the moat represented the encircling sea and the raised cathedral the mountain-dwelling of the gods? Or are such readings more the product of Western analysis and wishful thinking than the original intentions of their builders? The discussion here is opened by an architectural historian, who places city-planning firmly within the Western intellectual tradition, and considers it in particular as a product of Greek geometry. A series of regional specialists then take up the baton and assess the evidence for symbolic city planning in Egypt, the Roman world, South and Southeast Asia, and Mesoamerica. How far did cities of the Classical world conform to ideas set out by Aristotle and Vitruvius? Were the regulations of the Artashastra really adopted as a practical guide for city lay-out in South Asia? The balance of evidence — of what may have been intended, against what was actually laid out on the ground — provides fertile ground for a stimulating diversity of opinions.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.029 |
| Scholarly communication | 0.015 | 0.011 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".