Global urbanization, is it sustainable? The challenge to the UN World Urban Forum in Vancouver, 2006
Bibliographic record
Abstract
H. Peter OberlanderThe author is Professor Emeritus and founding Director of the Universityof British Columbia's School of Community and Regional Planning. Healso founded the UBC Centre for Human Settlements, Canada's legacyof HABITA T 1 976 Conference. He is currently the Senior Advisor tothe Commissioner General of WUF2006 and was a key organizer ofHABITAT 1976, the UN's first conference on Human Settlements.Professor Obertander was inducted into the Order of Canada in 1995and promoted to Officer in 2001, with the following Citation: * He is an im-portant advocate of sustainable urbanization - the process of improvingthe quality of our cities while promoting their sustainable growth. Widelyrespected by governments and international organizations, he served inthe mid-1990s as a Senior Advisor for the United Nations Commissionon Human Settlements. " The text that follows is a slightly revised andedited version of a paper presented at the international symposion on"The Natural City, " Toronto, 23-25 June, 2004, sponsored by the Univer-sity of Toronto's Division of the Environment, Institute for Environmental Studies, and the World Society for Ekistics.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.001 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.024 | 0.003 |
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".