The Urban Cliff Hypothesis and its relevance to ekistics
Bibliographic record
Abstract
The Cliff Ecology Research Group (CERG), Department of Integrative Biology, University of Guelph, Guelph, Ontario, Canada, has been in existence since 1985 when its members began working on the ecology of the Niagara Escarpment (fig. 1). In 1988 they discovered a stand of ancient trees growing on the cliffs and in 1989 they discovered that in fact the escarpment cliffs support the oldest and least disturbed forest ecosystem in Canada. Individual living trees older than 1,300 years are still present and the forest appears to be in steady state. CERG's work on the ancient trees led to the idea that cliffs serve as refuges for many species including ancient humans. That observation led to the development of the Urban Cliff Hypothesis that is described in this paper and was 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, and also led to the recent book entitled The Urban Cliff Revolution.
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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 | 0.000 | 0.001 |
| 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".