Argumente und Möglichkeiten für eine Quantifizierung und ein Monitoring der differenzierten Landnutzung
Bibliographic record
Abstract
The concept of differentiated land use was formulated already 50 years ago to preserve biodiversity and to maintain or restore the necessary landscape structure. Although it has been anchored in the Federal Nature Conservation Act, there is still no monitoring of its implementation, although the German Advisory Council on the Environment has been calling for this for 25 years. The paper argues that the technical prerequisites for monitoring the differentiated land use are ready today and discusses the conceptual steps necessary. It identifies several dimensions and proposes corresponding indicators of landscape structure, in particular the degree of diversification and the mixing of intensive land uses, the distribution of the size of intensively used areas, the proportion of semi-natural areas (at least 10 %) and the interconnected arrangement of semi-natural areas. Furthermore, the paper discusses suitable reference units and existing data. Finally, we identify remaining gaps in the data basis and discuss the question of defining target values.
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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 | 0.060 | 0.126 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.002 | 0.034 |
| Scholarly communication | 0.015 | 0.027 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".