Transaction costs for collaboration in the watershed management of the Cuyahoga River Area of Concern
Notice bibliographique
Résumé
This study examines the transaction costs of collaborative watershed management in the Cuyahoga River Area of Concern (AOC)—one of the 43 geographic areas designated by the U.S. and Canada Great Lakes Water Quality Agreement (GLWQA), where significant impairment of beneficial uses has occurred as a result of human activities. The Cuyahoga River is located in Northeast Ohio, the U. S. and flows through the City of Cleveland before draining into Lake Erie—one of the five Great Lakes of North America. The watershed is degraded due to municipal and agricultural discharges, streambank erosion, and contamination from urban and industrial sources. This research explores how a diverse group of stakeholders convened under the Cuyahoga River AOC Advisory Committee to share information, coordinate activities, agree on activities that restore beneficial uses, and support strategic management actions. In this study, 23 semi-structured interviews with members of the advisory committee were conducted between January 28, 2020 and April 20, 2020, with follow-up emails and phone calls as needed to corroborate information. A review of research articles and government documents supported the interviews, including United States Environmental Protection Agency (U.S. EPA) and Ohio Environment Production Agency (OEPA) reports on the GLWQA and Cuyahoga River Remedial Action Plans. A third source of data is from direct participant observation at quarterly meetings of the advisory committee during 2017–2020, binational AOC conferences in 2017 and 2019, and other professional events geared towards restoring the Cuyahoga River AOC in 2016–2020. Results help to explain the collaborative process within the advisory committee and measure the institutional performance of the advisory committee in terms of efficiency, equitability, accountability, and adaptability. Results of this study include a set of recommendations to help guide group structure and decision-making processes, including (1) employing best available technology to organize AOC events and disseminate information; (2) supporting new members with an orientation and/or mentor to clearly define formal and informal committee rules; (3) assuring equal access to detailed information on management action plans with a real time dashboard; (4) updating voting procedures and the prioritization of management actions; and (5) better incorporating underrepresented local communities and high-level decision makers from municipalities, government agencies, and nongovernmental organizations located within the Cuyahoga River AOC.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».