Place in Movement: Tracing Human-Altered Landscapes Along the Niagara Escarpment
Bibliographic record
Abstract
The Niagara Escarpment, a 440-million-year-old landform, cuts through a property owned by the University of Toronto in Caledon, Ontario in Canada. The property juxtaposes impacts from historical quarrying activity which burrowed directly into the Escarpment’s slope, the greater context of the region’s urban development demands, and the Escarpment’s identity as an ancient geological formation, ecological refugium, and old-growth forest housing ancient species such as Thuja occidentalis.This project explores the university’s responsibility in advocating for the protection of the Escarpment’s unique ecologic conditions, including the distinct cliff ecosystems and the novel successional plant communities evolving on sites of former quarry activities. Interventions on the trail system, cave bridges and lookouts, and the boardwalk and path system, along with guidance of signage and trail markers, will bring visitors to areas where former quarry activities sculptured the Escarpment’s limestone faces and are now reclaimed by a system of lush novel wetlands and habitats in evolutionary stages. Connecting to a system of existing public trails, this project leverages the university’s educational and recreational objectives to form new strategic partnerships with local conservancy groups, aiming at monitoring and managing access and habitat protection. ● Indigenous-led conservation efforts and partnerships with local conservancy groups are emphasized to enhance sustainability and stewardship ● Interventions were proposed on the trail system, cave bridges and lookouts, and the boardwalk and path system ● The interventions aim to balance the site’s educational and recreational use with the preservation of its delicate ecosystems
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".