Understanding material dependencies, adaptations and livelihoods in the Danube Delta: Implications for adaptive governance and knowledge integration
Bibliographic record
Abstract
We propose an approach to adaptive governance of social-ecological systems which can contribute to an advanced contextualization and specification of governance and adaptation by introducing three interrelated typologies in governance: typologies of livelihoods, of adaptations and of material dependencies. Applying these typologies can produce a sharper image of the social-ecological system, of human-environment relations, of problems and possible solutions. Empirically, we illustrate our framework with insights from the Romanian Danube Delta, an ecologically and culturally complex yet sensitive area, where adaptation issues are foregrounded on a regular basis. Using the typologies produces a re-interpretation of the coastal community as embedded in its ecological environment, the impact of that environment on the community and vice versa. A history of adaptations in two directions has to be clarified before a localized version of adaptive coastal governance can be considered. We discuss the value of the perspective for knowledge integration towards adaptation as well as the value for de-construction of existing patterns of integration and discursive dominance. • Diversity of perspectives on the entangling of social-ecological systems is valuable. • Typologies produces a reinterpretation of community and its ecological environment. • Many social-ecological relations are mediated through governance. • New social identities resulted from self-chosen and imposed adaptation.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.021 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".