Co-Production and Collaboration: Examining the Application of Co-Production of Knowledge Principles and Practices at the Arctic Rivers Summit in Anchorage, Alaska
Notice bibliographique
Résumé
<p dir="ltr" style="line-height: 1.38; text-indent: 36pt; margin-top: 0pt; margin-bottom: 0pt;"><span style="font-size: 12pt; font-family: 'Times New Roman'; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;">In the face of climate change impacts in the Arctic and sub-Arctic regions of Alaska and northwest Canada, there is a growing need to improve collaboration between Indigenous communities and western scientists to address multifaceted socio-environmental problems. These problems include shifts in the freezing of river-ice transportation corridors, permafrost thaw, and decreased salmon abundance in the Yukon River. These environmental problems pose drastic impacts for Indigenous communities in the region who depend on rivers for transportation, subsistence fishing, and cultural heritage. Addressing these challenges holistically and equitably requires employing a co-production of knowledge framework for producing useful and usable knowledge. This process requires high capacity for and commitment to building relationships between Indigenous Knowledge holders and western scientists. The Arctic Rivers Project is a multidisciplinary project led by Yukon River communities and organizations, the University of Colorado, Boulder, and the United States Geological Survey. The project attempts to employ a co-production of knowledge framework to understand climate change impacts in Alaska’s Yukon River basin with the goal of producing useful and usable knowledge.</span><strong id="docs-internal-guid-5b3086ff-7fff-17a6-0d73-720ca080a11e" style="font-weight: normal;"></strong> <p dir="ltr" style="line-height: 1.38; text-indent: 36pt; margin-top: 0pt; margin-bottom: 0pt;"><span style="font-size: 12pt; font-family: 'Times New Roman'; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;">In this work, I explore the application of co-production of knowledge principles and practices in the planning, preparation, and execution of the Arctic Rivers Summit, held by the Arctic Rivers Project in Anchorage, Alaska, December 6-8, 2022 to bring together Yukon River stakeholders and community members. I write a narrative of the preparation and sessions held at the Arctic Rivers Summit, analyzing them for their applications of co-production of knowledge principles and practices. I then explore the extent to which co-production of knowledge principles were employed, the scalability of co-production efforts, and challenges in co-production of knowledge between western scientists and Indigenous communities. In my analysis, I found that co-production practices were utilized throughout the process, beginning with the event’s co-production by the Arctic Rivers Project research team, Indigenous Advisory Council, and the Institute for Tribal Environmental Professionals. The processes that were used in planning, preparing for, and executing the Arctic Rivers Summit serve as an example for how academic institutions can work to integrate co-production of knowledge processes and practices into events and research projects with Indigenous communities.</span>
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Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| 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) | 0,002 | 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 ».