Sustainable Future 2030: Embracing Nature Positive Strategies
Bibliographic record
Abstract
The ‘nature positive’ paradigm represents an ambitious and transformative agenda in global sustainability, advocating for a world where human activities actively enhance biodiversity whilst equitably advancing human prosperity. This concept has garnered support from leading global institutions, businesses, and policymakers, as evidenced by the G7's ‘2030 Nature Compact’ and the Kunming-Montreal Agreement. These developments reflect a growing recognition of the deep interdependence between human prosperity and ecological health. Yet, the application of practical ‘nature positive’ strategies is challenging particularly the development and application of robust indicators to measure progress and ensure equitable implementation across variable socio-economic contexts. The primary socio-political obstacle lies in the continued prioritization of immediate economic gains and consumer habits over the planet's long-term environmental and economic well-being. This trajectory exacerbates the looming ecological and climatic crisis. As the ‘nature-positive’ concept gains momentum, it invites a comprehensive re-evaluation of our relationship with nature, highlighting the imperative for a harmonious coexistence between economic development and ecological restoration. The journey towards a ‘nature positive’ future is not only a conservationist pursuit but a necessary evolution towards a sustainable and resilient global economy, crucial for the well-being and future generations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".