PROPOSED STANDARDS AND GUIDELINES FOR PRIVATE NATURE RESERVES IN THE NORTHERN GREAT PLAINS
Bibliographic record
Abstract
More than three-quarters of the land in the Northern Great Plains is privately owned and less than 2% of the region is in public protected areas; therefore, sound private-land management is critical for restoring and conserving the region’s biodiversity. Although considerable progress has been made in recent years in fostering and assembling nature reserves on private lands in various regions of the world, this approach has received little attention in North America, including the Northern Great Plains. We review here recommendations, trends and issues related to private protected areas globally and in Canada and the United States. We then discuss socioeconomic and ecological conditions that deserve particular attention in creating private protected areas, which we prefer to call “private nature reserves,” in the Northern Great Plains. We conclude with proposed standards and guidelines for the establishment and recognition of private nature reserves in the region.
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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 | 0.047 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.008 | 0.005 |
| Research integrity | 0.016 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".