An agenda for research and action toward diverse and just futures for life on Earth
Bibliographic record
Abstract
Decades of research and policy interventions on biodiversity have insufficiently addressed the dual issues of biodiversity degradation and social justice. New approaches are therefore needed. We devised a research and action agenda that calls for a collective task of revisiting biodiversity toward the goal of sustaining diverse and just futures for life on Earth. Revisiting biodiversity involves critically reflecting on past and present research, policy, and practice concerning biodiversity to inspire creative thinking about the future. The agenda was developed through a 2-year dialogue process that involved close to 300 experts from diverse disciplines and locations. This process was informed by social science insights that show biodiversity research and action is underpinned by choices about how problems are conceptualized. Recognizing knowledge, action, and ethics as inseparable, we synthesized a set of principles that help navigate the task of revisiting biodiversity. The agenda articulates 4 thematic areas for future research. First, researchers need to revisit biodiversity narratives by challenging conceptualizations that exclude diversity and entrench the separation of humans, cultures, economies, and societies from nature. Second, researchers should focus on the relationships between the Anthropocene, biodiversity, and culture by considering humanity and biodiversity as tied together in specific contexts. Third, researchers should focus on nature and economies by better accounting for the interacting structures of economic and financial systems as core drivers of biodiversity loss. Finally, researchers should enable transformative biodiversity research and action by reconfiguring relationships between human and nonhuman communities in and through science, policy, and practice. Revisiting biodiversity necessitates a renewed focus on dialogue among biodiversity communities and beyond that critically reflects on the past to channel research and action toward fostering just and diverse futures for human and nonhuman life on Earth.
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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 | 0.119 | 0.053 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.020 | 0.046 |
| Scholarly communication | 0.031 | 0.050 |
| Open science | 0.006 | 0.029 |
| Research integrity | 0.035 | 0.034 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".