Operationalizing transformative change for business in the context of nature positive
Bibliographic record
Abstract
The Kunming-Montreal Global Biodiversity Framework (GBF) set a specific target for reducing the private sector’s negative impacts on biodiversity and increasing positive impacts, as part of efforts to halt and reverse biodiversity loss. Meanwhile, ‘Nature Positive’ is emerging as an ambitious rallying call for mainstreaming the GBF. Merely tinkering with business-as-usual will not deliver these ambitions, and so calls for transformative change in business's relationship with biodiversity are increasing. However, there remains a lack of clarity on how to operationalize transformative change in the context of Nature Positive and the GBF, particularly how to develop meaningful actions and targets. This gap risks confusion, greenwashing, and failure to achieve global goals. This perspective draws on existing literature on social change to offer a practical framework for understanding and operationalizing transformative change for business and nature. We define and describe the role of transformative change within a Nature Positive ambition and summarize different types and scales of actions that companies could take, which we illustrate with case study examples. This framework could help with planning coordinated and mutually reinforcing actions towards transformative change, setting ambitious targets, and holding companies accountable to ‘transformative’ claims. However, all such plans and claims should be founded on abatement of new and on-going negative impacts first and foremost through implementing the mitigation hierarchy. We invite companies to test our framework for their own planning, decision-making and disclosures, to drive transformative change for a safe and just future.
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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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".