Operationalizing transformative change for business in the context of Nature Positive
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Kunming-Montreal Global Biodiversity Framework (GBF) includes a specific target for reducing businesses' negative impacts on biodiversity and increasing their positive impacts to contribute toward the GBF mission and vision. "Nature Positive" is also emerging as a rallying call for mainstreaming the GBF. Merely tinkering with business as usual will not deliver these ambitions; transformative change is needed. However, how to operationalize transformative change toward Nature Positive and the GBF through meaningful actions and targets remains unclear, risking confusion, greenwashing, and failure to achieve global goals. This perspective draws on literature on social change to offer a practical framework for understanding and operationalizing transformative change for business toward a Nature Positive future. We define and describe the role of transformative change within a Nature Positive ambition and summarize the different types and scales of actions companies could take. This framework could help to plan mutually reinforcing actions and improve accountability for Nature Positive claims.
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.
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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it