Watershed Governance for Rural Communities: Aligning Network Structure with Stakeholder Vision
Bibliographic record
Abstract
Water governance often adopts one of two end-member frameworks: (a) centralized, command-control structures, or (b) distributed–collaborative networks. The former typifies the traditional style of water governance that has reigned for the past century, whereas the latter is increasingly touted as a panacea to the evolving challenges of water resource management in a time of rapidly changing drivers (e.g., climate change, urbanization). This study applies Social Network Analysis (SNA) to two case-study watersheds in south-central British Columbia in order to assess the (mis)alignment between water governance network structure and stakeholder objectives regarding adaptation to the pressures imposed by climate change. The results indicate that rural, water-scarce regions continue to be burdened by centralized, command-control style structures that reinforce the status quo in watershed governance (Neef, 2009). This reality marginalizes stakeholders at the peripheries of the network, who may represent a silent but significant voice in regard to future visions for watershed governance. The management of common-pool resources in rural areas will likely remain a difficult challenge without social networks that are designed strategically so as to become better aligned with stakeholder visions. Keywords: adaptive; bridging; knowledge transfer; learning; social network ------------------------------------------------------------- Résumé La gouvernance des ressources en eau adopte souvent une des deux structures diamétralement opposées: (a) centralisée, des structures de commande de contrôle, ou (b) distribuée - réseaux collaboratifs. La première caractérise le style traditionnel de gouvernance d'eau qui a régné pendant le siècle passé, tandis que la dernière est de plus en plus vantée comme la panacée aux difficultés rencontrées dans la gestion des ressources en eau, en période de facteurs de changements rapides (ex.: changements climatiques, urbanisation). Cette étude applique la méthode de l'analyse des réseaux sociaux (ARS) à deux études de cas de bassins hydrologiques, dans le centre-sud de la Colombie-Britannique afin d'évaluer l'alignement et le désalignement entre la structure des réseaux de la gouvernance de l'eau et les objectifs des intervenants clés, pour toutes les questions relatives aux pressions imposées par le changement climatique. Les résultats indiquent que les régions rurales, pauvres en eau, continuent d'être accablées par un style de structures de commande de contrôle centralisé qui renforce le statu quo dans les gouvernances de bassins (Neef, 2009). Cette réalité marginalise les intervenants clés à la périphérie du réseau, qui peut représenter une voix faible mais cependant significative au regard de la vision future de la gouvernance des bassins. La gestion des ressources collectives dans les zones rurales demeurera probablement un défi difficile sans réseaux sociaux désignés stratégiquement dans le but d'être mieux enlignés avec les visions des intervenants.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| 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".