Framework for a national nature strategy:facilitating the development of national nature strategies that are aligned with the Convention on Biological Diversity
Bibliographic record
Abstract
The economies of African countries, like those of countries in other global regions, are heavily reliant on natural resources. Nature loss and degradation pose significant risks for economic development and well-being. Investments to protect and restore natural environments can help safeguard African and other global regions from risks associated with environmental degradation and unlock new economic opportunities. A national nature strategy can facilitate countries’ efforts to navigate an increasingly complicated normative landscape characterized by numerous compliance obligations and commitments. In this report, the authors present a framework that can facilitate efforts by African and other countries to draw up and implement national nature strategies. The framework provides start-to-finish guidance and covers the implementation of nature assessments, the establishment of a national vision and related targets, the development of a strategy to deliver on those targets, strategy implementation, the exploitation of nature-related opportunities, the management of nature-related risks, and compliance with international obligations, such as those stemming from the Kunming Montreal Global Biodiversity Framework and from national biodiversity strategies and action plans. The strategy was developed in collaboration with a wide range of stakeholders, including policymakers, nature experts and representatives of non-governmental and multilateral organizations. The framework comprises four components, namely: Baseline and ambition: reasons for a national nature strategy and outcomes to aim for; Initiatives: actions to take to achieve the outcomes; Instruments: incentivizing action to achieve desired outcomes; and Governance and implementation: planning and implementing the strategy and assigning responsibilities. The aim of the framework is to accelerate the development of national nature strategies. It has been drafted in line with the provisions of the Kunming Montreal Global Biodiversity Framework and a few national biodiversity strategies and action plans and provides systematic guidance that countries may find helpful when formulating their national nature strategies.
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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 | 0.044 | 0.024 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.008 | 0.011 |
| Scholarly communication | 0.018 | 0.010 |
| Open science | 0.006 | 0.012 |
| Research integrity | 0.019 | 0.012 |
| Insufficient payload (model declined to judge) | 0.010 | 0.005 |
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".