Design and management ideas for Henteleff Park, Winnipeg, Manitoba
Bibliographic record
Abstract
As the earth’s climate continues to change and natural ecosystems become degraded, urban landscapes hold particular potential to address these issues. Henteleff Park is a unique landscape in Winnipeg, Manitoba as a remnant riparian forest, tree nursery, and living collection of trees. It holds potential as a public space for education, experimentation, sustainability and ecology, and as an arboretum. This practicum aims to develop design and management ideas for Henteleff Park based on an analysis of the site and surrounding area, research, precedent study, and the goals of the Henteleff Park Foundation. The project is oriented around the following 5 objectives: 1) Embrace change: Embrace the dynamic nature of plants and their changes in form and function through seasons and time, and adapt to a changing climate. 2) Education and Experimentation: Create opportunities for observation, education, research and hands-on experimentation with plants. 3) Accessibility and Connectivity: Improve the ability for people, fauna and flora to move through the space. Strengthen connectivity between the park and adjacent spaces. 4) Sustainability and Ecology: Improve the site’s environmental sustainability including carbon sequestration, water and air filtration, erosion mitigation, and urban heat island mitigation. Improve ecological health and functionality. 5) Transform the park into an Arboretum: Build on the existing assets of Henteleff Park to develop the space as an Arboretum.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.027 | 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".