The Biodiversity Commitments of Earth’s Keystone Corporations: Current Limitations, Untapped Potential, and Future Directions
Bibliographic record
Abstract
Over the past 50 years, large transnational "keystone" corporations have concentrated power and gained significant influence over the world's resource reserves, production and trade. The Kunming-Montreal Global Biodiversity Framework emphasizes the crucial role of businesses in setting and disclosing targets to mitigate their impact on nature. In this study, we identified 180 keystone corporations from highly concentrated sectors with significant environmental impacts and assessed their biodiversity commitments. Our findings reveal that while 79% of firms have made some form of biodiversity pledge, only 13% have reported sufficiently detailed, transparent and specific commitments (“robust commitments”) to allow others to assess if the targets have been met – a key prerequisite of accountability. We discuss future directions and underscore the urgent need for companies, governments, and civil society – including the research community – to work collaboratively to develop, implement, and monitor credible corporate strategies that drive meaningful action for nature.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| 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".