Turning the tide in estuary governance through collaboration? A systematic review, meta-synthesis, and conceptual framework
Bibliographic record
Abstract
Estuaries are contested spaces and subject to highly variable environmental conditions and increasing human and climate change impacts. This leads to socio-economic and environmental conflicts and raises the question of how to achieve effective estuary governance that is capable of dealing with existing and future challenges. This article presents a systematic literature review and meta-synthesis of estuary governance using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) 2020 protocol. The review shows that, starting in 2010, research on estuary governance has slowly developed since then in various scientific disciplines, such as the environmental sciences, social sciences, and studies dealing with environmental governance. In recent years, this research has gained momentum, although it continues to exhibit notable terminological and conceptual ambiguity. In the context of this ambiguity, collaborative governance, a theory-based approach, provides both a conceptual foundation and an analytical lens to address and structure key aspects identified in the review. Conceptually seen, collaborative governance presents an approach in which state and non-state stakeholders work together to balance competing interests and try to achieve a common goal. Although some aspects, such as stakeholder engagement and knowledge integration, have—albeit mostly unintentionally—already been incorporated into the approach of estuary governance studies, there still exists a lack of studies applying collaborative governance in the field. To fill this gap, the paper proposes a conceptual framework for collaborative estuary governance informed by already existing approaches. We thus expand the “system context” of current approaches for estuarine realities by including concepts such as “environmental context” and “conflict context.” In brief, the paper suggests a structural re-conceptualization of estuary governance, as seen through a collaborative governance lens.
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 | 0.212 | 0.358 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.014 |
| Bibliometrics | 0.035 | 0.030 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.014 | 0.017 |
| Open science | 0.006 | 0.010 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".