Bibliographic record
Abstract
The author is a Professor of Geography at the University of Toronto and former Director of the Institute for Environmental Studies. His research interests are in urban environmental management/urban infrastructure; adaptation to climate change; catastrophes, environmental liability and the insurance industry; and risk analysis and environmental finance. He has extensive overseas experience, especially in Africa and China. He was the Principal Investigator for the GIS-based Soil Erosion Management Project in North China and for the Toronto component of the Sustainable Water Management Project in the Beijing-Tianjin Region, both funded by CIDA. He has held teaching appointments at North-western University, McMaster University and Ibadan University, and has also taught short courses in Senegal, Malawi and Vietnam. He holds degrees in geography from Oxford (B.A., 1965), Pennsylvania State University (M.Sc., 1967) and Bristol University (Ph.D, 1971). His most recent books are Building the Ecological City, published by Woodhead Publishing in 2002 and Environmental Finance: A Guide to Environmental Risk Assessment and Financial Products (with Sonia Labatt) published by Wiley in 2002. The text that follows is an edited version of a paper presented at the international symposion on "The Natural City," Toronto, 23-25 June, 2004, sponsored by the University of Toronto's Division of the Environment, Institute for Environmental Studies, and the World Society for Ekistics.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".