Supporting native grasslands in Canada: Lessons learned and future management of the Prairie Pastures Conservation Area (PPCA) in Saskatchewan
Bibliographic record
Abstract
Temperate grasslands are the most endangered and least protected biome in the world. Few significant parcels remain and strategies for ongoing protection are critical for conservation efforts worldwide. In southwestern Saskatchewan, three contiguous blocks of native grassland, known as the Prairie Pastures Conservation Area, are federally managed by Environment and Climate Change Canada. Previously, the 800‐km2space was managed by the Department of Agriculture as public rangeland in the Prairie Farm Rehabilitation Agency (PFRA). We interviewed 11 individuals, including NGO representatives and pasture patrons, familiar with the PFRA at a native prairie/grassland conference to enhance our understanding of the importance of the agency and the lands in the province to them, as well as to Canada and globally. Themes that emerged included benefits of historic PFRA management, reservations about privatization of pasturelands, and worries about mismanagement. We take these themes and build them into our recommendations for what Environment and Climate Change Canada should do with the Prairie Pastures Conservation Area going forward: enhance Indigenous collaboration, establish a conservation network, and increase public use and awareness.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".