Re-conceptualizing the Anthropocene. A call for collaboration
Bibliographic record
Abstract
Since it was first proposed in 2000, the concept of the Anthropocene has evolved in breadth and diversely. The concept encapsulates the new and unprecedented planetary-scale changes resulting from societal transformations and has brought to the fore the social drivers of global change. The concept has revealed tensions between generalized interpretations of humanity’s contribution to global change, and interpretations that are historically, politically and culturally situated. It motivates deep ethical questions about the politics and economics of global change, including diverse interpretations of past causes and future possibilities. As such, more than other concepts, the Anthropocene concept has brought front-and-center epistemological divides between and within the natural and social sciences, and the humanities. It has also brought new opportunities for collaboration. Here we explore the potential and challenges of the concept to encourage integrative understandings of global change and sustainability. Based on bibliometric analysis and literature review, we discuss the now wide acceptance of the term, its interpretive flexibility, the emerging narratives as well as the debates the concept has inspired. We argue that without truly collaborative and integrative research, many of the critical exchanges around the concept are likely to perpetuate fragmented research agendas and to reinforce disciplinary boundaries. This means appreciating the strengths and limitations of different knowledge domains, approaches and perspectives, with the concept of the Anthropocene serving as a bridge, which we encourage researchers and others to cross. This calls for institutional arrangements that facilitate collaborative research, training, and action, yet also depends on more robust and sustained funding for such activities. To illustrate, we briefly discuss three overarching global change problems where novel types of collaborative research could make a difference: (1) Emergent properties of socioecological systems; (2) Urbanization and resource nexus; and (3) Systemic risks and tipping points. Creative tensions around the Anthropocene concept can help the research community to move toward new conceptual syntheses and integrative action-oriented approaches that are needed to producing useful knowledge commensurable with the challenges of global change and sustainability.
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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 | 0.067 | 0.075 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.016 | 0.020 |
| Science and technology studies | 0.011 | 0.080 |
| Scholarly communication | 0.038 | 0.088 |
| Open science | 0.004 | 0.029 |
| Research integrity | 0.010 | 0.016 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".