Bibliographic record
Abstract
The author, immediate Past President of the World Society for Ekistics, is an architect and urban planner with extensive national and international experience in urban developments of varying scales. Founder of his own architectural firm in 1956, he has also served since 1972 as President of Leman Group Inc., an urban planning and development consulting firm based in Toronto, Canada. Projects have included the planning of a new capital city, new communities, towns and cities; ports; regional economic development plans; self-help housing programs; and economic and regional structure plans, as well as programming and project management Since 1994, he has also served as Chairman and CEO of Urbanitas Worldwide Inc., a company dedicated to planning and development of human settlements in the developing world. Over the course of his career, Mr Leman has been invited to speak in 48 countries around the world. He holds the distinction of being one of the few Canadians listed in the International Who's Who 2000, published in London, UK and was, in October 2000, nominated and elected a Fellow of the World Innovation Foundation.
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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.020 |
| Scholarly communication | 0.011 | 0.016 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.020 | 0.001 |
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".