Deliverable 7.14 Proceedings from community-based monitoring and citizen science workshopsin the Arctic 2017-2021
Notice bibliographique
Résumé
One of the aims of INTAROS is to build additional capacity within Indigenous and civil society organizations, government agencies and scientists on community-based and citizen science observing in the Arctic. There is no single ‘right’ way of undertaking community-based observing. The approach will vary and what is suitable to ensure effective monitoring will change from one place to the next although there are a number of features which, in many cases, will be shared. One of the most effective ways to build capacity in community-based observing is through bringing people together and enabling the participants to share their experiences related to community-based observing, discussing and agreeing on what works, when and why. Over the course of the INTAROS project, from Dec. 2016 to May 2021, the project has organized or co-organized 40 workshops, dialogue meetings, seminars and other events on community-based monitoring (CBM) in the Arctic and Sub-Arctic. The events have been attended by at least 600 people, including representatives from five Arctic Indigenous Peoples (Inuit, Sami, Evenk, Gwi ́chin and Komi Izhma), and citizens of all eight Arctic nations. It is noteworthy that there have been some 200 youth among the participants, mostly from Arctic Russia. The events have contributed to >400pages of proceedings, technical reports and publications on community-based observing in the Arctic. Summaries of the discussions at most of these events have already been widely circulated. In this document, we highlight 12 of the events on community-based observing, including seven workshops, one international conference side-event, three online meetings,and one in-service training course. These events were held in Alaska, Canada, Greenland, Norway, Germany, Russia, and online during Covid-19. In many discussion sessions at the events, participants were concerned about how to connect CBM programs with top-down observing approaches and associated management decision-making processes. In the last part of this document, we therefore discuss the challenges and opportunities for connecting CBM programs with top-down observing approaches and associated management decision-making processes, drawing on a review by Hajo Eicken and colleagues (2021). Connecting CBM programs and top-down observing approaches can lead to improved information products and enhanced efficiency and sustainability of observing programs (Eicken et al. 2021). It can also promote stronger linkages between CBM programs and natural resource management decision-making processes. Core principles central to such linkages are: 1) matching observing program aims, scales, and ability to act on information; 2) matching observing program and community priorities; 3) fostering compatibility in observing methodology and data management; 4) respect for Indigenous intellectual property rights and the implementation of Free, Prior, and Informed Consent; 5) creating sufficient organizational support structures and ensuring that CBM programs link with decision-making processes on natural resource management; and 6) ensuring sustained community members’ commitment. In the document, we present and discuss suitable interventions to overcome challenges in adhering to these six principles.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,006 | 0,003 |
| Science ouverte | 0,002 | 0,007 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,474 | 0,331 |
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 source (Gemma direct ou Codex distillé), 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 ».