Bibliographic record
Abstract
The author served as a Member of the Canadian Parliament from 1993 to 2001. He founded two political parties - the Reform Party of Canada and the Canadian Reform Conservative Alliance. He served as Leader of the Opposition from 1997 to 2000 and was also his party's critic for Science and Technology. Since retirement from Parliament in 2001, Mr Manning has become a Senior Fellow of two major Canadian research bodies, the Fraser Institute and the Canada West Foundation. He is also a Distinguished Visitor and lecturer at the University of Calgary and the University of Toronto. In 2002 he released a book entitled Think Big (published by McClelland &Stewart). He continues to write, speak, and teach on various subjects.The text that follows is an edited and revised 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 ofthe 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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.024 | 0.009 |
| Scholarly communication | 0.011 | 0.002 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.023 | 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".