The seeds’ substrate: a concept to understand how transformations toward Good Anthropocenes can be enabled
Bibliographic record
Abstract
The importance of connectedness in laying the ground for social-ecological transformations or in spreading new ideas and practices for transformation is increasingly recognized. However, the role of networks in supporting the emergence and growth of seeds (initiatives with the potential to positively shape the future) has not yet been comprehensively studied empirically. To this end, we introduce a novel concept, the seeds’ substrate, to characterize: (1) the relationships among a network of seeds, (2) the support needed for seeds to appropriately scale and coalesce, and (3) the actors that enable and provide support. The seeds’ substrate concept was theoretically informed and empirically derived by using a case study of an ongoing coalescing process. On this basis, we derived several categories and definitions for seeds interactions, types of support, and supporting actors that collectively constitute the seeds’ substrate. Specifically, we identified seven types of interactions between seeds, nine types of support, and 14 different categories of supporting actors. Furthermore, we presented a multi-level network approach to analyze the seeds’ substrate and test specific hypotheses within this modeling approach. By putting the seeds’ substrate concept into practice in an ongoing coalescence process involving 11 seeds around the small-scale fisheries food system in Uruguay, we identified the network of seeds and the constellations of actors and interactions that preceded efforts to deliberately foster a seed coalition. This allowed us to anticipate synergies and conflicts and to identify key supporting actors that structure the seed substrate. In addition, we derived a comprehensive baseline against which to quantitatively compare the unfolding of the coalescence process over time. This paper contributes to filling a gap in the Seeds of Good Anthropocenes literature and unpacks a key but largely unexplored subprocess of its theory of change: the transition from periods of experimentation to periods of coalescence. We expect the seeds’ substrate concept to be useful in a wide and diverse range of social-ecological contexts.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.025 |
| Scholarly communication | 0.008 | 0.017 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".