Social-Ecological Systems Insights for Navigating the Dynamics of the Anthropocene
Bibliographic record
Abstract
Social-ecological systems (SES) research offers new theory and evidence to transform sustainable development to better contend with the challenges of the Anthropocene. Four insights from contemporary SES literature on ( a) intertwined SES, ( b) cross-scale dynamics, ( c) systemic tipping points, and ( d) transformational change are explored. Based on these insights, shifts in sustainable development practice are suggested to recognize and govern the complex and codeveloping social and ecological aspects of development challenges. The potential susceptibility of SES to nonlinear systemic reconfigurations is highlighted, as well as the opportunities, agency, and capacities required to foster reconfigurative transformations for sustainable development. SES research proposes the need for diverse values and beliefs that are more in tune with the deep, dynamic connections between social and ecological systems to transform development practice and to support capacities to deal with shocks and surprises. From these perspectives, SES research offers new outlooks, practices, and novel opportunity spaces from which to address the challenges of the Anthropocene.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.002 | 0.014 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".