Scientific mobilization of keystone actors for biosphere stewardship
Bibliographic record
Abstract
The biosphere crisis requires changes to existing business practices. We ask how corporations can become sustainability leaders, when constrained by multiple barriers to collaboration for biosphere stewardship. We describe how scientists motivated, inspired and engaged with ten of the world's largest seafood companies, in a collaborative process aimed to enable science-based and systemic transformations (2015-2021). CEOs faced multiple industry crises in 2015 that incentivized novel approaches. New scientific insights, an invitation to collaborate, and a bold vision of transformative change towards ocean stewardship, created new opportunities and direction. Co-creation of solutions resulted in new knowledge and trust, a joint agenda for action, new capacities, international recognition, formalization of an organization, increased policy influence, time-bound goals, and convergence of corporate change. Independently funded scientists helped remove barriers to cooperation, provided means for reflection, and guided corporate strategies and actions toward ocean stewardship. By 2021, multiple individuals exercised leadership and the initiative had transitioned from preliminary and uncomfortable conversations, to a dynamic, operational organization, with capacity to perform global leadership in the seafood industry. Mobilizing transformational agency through learning, collaboration, and innovation represents a cultural evolution with potential to redirect and accelerate corporate action, to the benefit of business, people and the planet.
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".