Bibliographic record
Abstract
As a documentation and communication vehicle - part of a broader effort of the Athens Center of Ekistics (ACE) to contribute to the development of a sound approach to the field of Human Settlements - Ekistics makes itself available as a free forum for the exposure of ideas and experiences from anywhere to everywhere, provided they are relevant and transferable. In this effort, writings of members of the World Society for Ekistics (WSE) have quite frequently been considered and published in Ekistics. How could our attitude be different in cases of collective efforts of the WSE such as its meetings last year in Berlin (24-28 October, 2001) with the title "Defining Success of the City in the 21st Century"? Actually, we have reported on such events on various occasions in the past, the most recent being in vol. 64, no. 385/386/387, July/August-Sept./Oct.-Nov./Dec.1997 and vol. 65, no. 388/389/390, Jan./Feb.-Mar./Apr.-May/June 1998 on "Mega-Cities ...and Mega-City Regions", a conference of which the WSE was a co-sponsor together with Tsinghua University, Beijing, China and the University of British Columbia, Canada.
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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.387 | 0.285 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".