Out to pasture: exploring use, value, and meaning in Saskatchewan’s former public pastures
Bibliographic record
Abstract
Although there is an ever-growing body of evidence on the ecological value of grasslands, and increasing concern for what remains, loss of native prairie continues. This practicum traces the course of this loss over the last 150 years, in part by looking at the history of the former public pastures of Saskatchewan. As some of the largest remnants of native prairie in the province, the pastures are examples of our changing values and perception of the prairie landscape, but they are also places of great potential for ecological engagement and education about the local landscape. In this way, they become a lens through which to view both our recent ecological and social past, and our possible future. Working with concepts from the field of environmental aesthetics, this practicum examines the role that Landscape Architecture can play in supporting grassland conservation efforts. In order to save the prairie that remains, we need more people to want to save it, and this practicum explores how to reveal the gifts of the grasslands to a greater part of the population. In doing so, it navigates how design can help to save an endangered landscape. While the work is focused on prairie remnants of Saskatchewan, the relationship between design and conservation could be expanded and applied beyond the provincial borders.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".