Benefits of federal community pastures on the prairies
Bibliographic record
Abstract
In the wake of widespread soil erosion, during the 1930s, the federal governments passed the Prairie Farm Rehabilitation Administration (PFRA) act, establishing the agency, and through it a system of community pastures in the three prairie provinces. At present, PFRA operates 87 such pastures. The major motivation for this program was to reduce soil erosion through some careful land management practices, thereby enabling them to be a source of summer pasture for cattle grazing. This was seen as fostering greater economic security, stability and diversification in the region. Over time, many other uses of community pastures have emerged. Although grazing and breeding function has remained prominent, many other uses have become important enough so as not be totally ignored. Some of the notable uses include: wildlife and waterfowl habitats, recreational activity, preservation of biodiversity, preservation of fragile ecosystems, conservation of heritage sites, research activity, among others. In order to determine these uses, a survey of PFRA community pastures was undertaken during the summer of 2000. The results of this survey indicate that although grazing and breeding activities are still the major economic activities on these community pastures, the Canadian and the Prairie society benefits from these pastures in a significant manner. This study suggests that the PFRA community pastures are more than a place for farmers to leave their cattle for the summer period; they provide several benefits to local communities, and other members of the society through ecosystem functions, and other use and non-use related activities.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".