Rangeland, livestock and herders revisited in the Northern Pastoral Region of China
Bibliographic record
Abstract
Rangelands, which comprise more than 40 percent of China’s land surface area, are an important natural resource that provides a direct livelihood for at least 39 million people. Although the importance of rangelands has been recognized for millennia, during the latter part of the 20th Century China’s rangelands have been subject to over-use by a growing population that is dependent on this natural resource for their livelihood and land-use changes that have diminished productivity and promoted degradation. The first internationally funded agricultural project was initiated in the Inner Mongolian Autonomous Region in 1981. In 1985, the Yihenoer Pilot Demonstration Area was established to demonstrate methods of rangeland management and livestock production facilitating sustainable use of rangelands. An ecological inventory of rangeland vegetation compiled over three years from ecological monitoring points indicated that rangeland condition was degrading. The primary reasons for deteriorating rangeland condition were overstocking and conversion of rangeland to rainfed cropland. In 2003, the Yihenoer Pilot Demonstration Area was revisited by Canadian and American range scientists. Evaluation and comparison with information obtained in 1987 indicated that rangelands of the Yihenoer Pilot Demonstration Area had continued to degrade, grass steppe rangelands were less productive, and that conversion of rangelands to rainfed cropland was continuing. The authors recommend that a “bottom-up” rangeland management planning program designed to integrate actual land users with well defined and rational “top-down” government agricultural policies be implemented in the northern pastoral region of China or degradation and loss of rangelands will continue.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".