Geodiversity in Nature: Improving Natural Heritage Management 
Bibliographic record
Abstract
Awareness is increasing amongst decision makers that societal challenges such as climate change, water resource management, biodiversity loss, poor soil health and air quality are interlinked. In contrast the holistic approach to Nature by pioneering 18th century natural scientists where biotic and abiotic components were interdependent, modern western science has evolved into specialised scientific disciplines. Today, science influenced global accords such as the Paris Agreement on climate change, Kunming-Montreal Global Biodiversity Framework and numerous United Nations Sustainable Development Goals place great emphasis on the biotic components of the natural world. Strategies and legislation at national level generally follow this trend and influence natural heritage management approaches.Case studies from the Chablais UNESCO Global Geopark in France illustrate the impact of a transdisciplinary approach to natural heritage management where both biotic and abiotic factors are considered. The explicit inclusion of geodiversity informed stakeholder decisions over matters such as the choice of legal conservation measures, the definition of protected area limits and content for public communication programs. Different decisions were taken as a result of this inclusive approach to Nature in the municipalities of Montriond and La Baume. The ongoing work in the Chablais region confirms the need for scientists, natural heritage managers and politicians to share a common understanding of nature and ecosystems that explicitly includes geodiversity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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; both teacher heads agree on what is shown here.
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".