Cities are successful because they are civic: The 2004 C.A. Doxiadis Lecture
Bibliographic record
Abstract
The decision for the organization annually of a C.A. Doxiadis Lecture to honor the memory of the founder of Ekistics, was taken at the WSE meetings in _el_kovice, Czech Republic, in 2000. The series is meant to invite distinguished experts in any professional field which may be considered as directly or indirectly contributing to ekistics, to expose their ideas on any theme of their preference. Reference to C.A. Doxiadis or ekistics is not required, although any such reference is not excluded. The program for this year's lecture scheduled to take place at 19.30 hrs on 24 June was as follows: Chairman: Alexander B. LemanIntroduction: Ingrid Leman StefanovicLecturer: Hon. David CrombieTheme: "Avoiding the 'dark age ahead' " The lecture was delivered in the Medical Sciences Auditorium and was followed by a lively discussion. *An edited version of Mr Crombie's presentation is produced on the opposite page entitled "Cities are successful because they are civic." The WSE President, Alexander B. Leman, offered the speaker the four books by C.A. Doxiadis which were presented in 1976, one year after his death, by the then President of WSE, Professor R. Buckminster Fuller, at the Assembly of the United Nations Conference on Human Settlements - Habitat I in Vancouver.
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.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.014 | 0.007 |
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".