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Understanding material dependencies, adaptations and livelihoods in the Danube Delta: Implications for adaptive governance and knowledge integration

2025· article· en· W4409202692 on OpenAlexaff
Kristof Van Assche, Petruţa Teampău, Natașa Văidianu

Bibliographic record

VenueOcean & Coastal Management · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicCoastal and Marine Management
Canadian institutionsUniversity of Alberta
FundersMinisterul Cercetării şi InovăriiMinisterul Cercetării, Inovării şi Digitalizării
KeywordsLivelihoodCorporate governanceDeltaAdaptation (eye)Environmental resource managementGeographyEnvironmental planningAdaptive capacityBusinessPolitical scienceClimate changeEcologyEnvironmental scienceAgricultureBiologyEngineeringArchaeology

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.940
Threshold uncertainty score0.636

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.041
GPT teacher head0.256
Teacher spread0.214 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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