Establishing a Municipal Climate Network in Atlantic Canada
Notice bibliographique
Résumé
Communities in Canada have influence over nearly 50% of Canadian greenhouse gas emissions and stand on the frontlines of climate change impacts. In order to meet energy objectives, continued coordinated action at the municipal level is essential. However, many municipal governments are constrained with regard to both human and financial capacity. These constraints reduce the ability of communities to seek out the necessary information on best practices and available funding to drive needed changes. The Municipal Energy Learning Group in Nova Scotia serves as a resource for knowledge mobilization among municipal staff and for these staff members to gather relevant information, learn about successful plans, visit projects in action, and network with their colleagues. For the past three years, with support from the Nova Scotia Department of Energy and Mines, QUEST (Quality Urban Energy Systems of Tomorrow) has experimented with various methods of bringing municipal staff from different local governments together, including webinars, facilitated peer-to-peer meetings, workshops, and study tours. Facilitating this group has allowed for an identification of trends in the barriers and opportunities faced by municipalities with regard to climate change, but also in the effectiveness of this model in delivering benefits to the members. The use of inspiration and celebration of success has been an important factor in affecting change. Also, the involvement of representatives from multiple departments has shown that everyone has valuable experience to share and increased engagement and knowledge transfer. The Municipal Energy Learning Group (MELG) in Nova Scotia serves as a resource for knowledge mobilization among municipal staff and for these staff members to gather relevant information, learn about successful plans, visit projects in action and network with their colleagues. For the past three years, with support from the Nova Scotia Department of Energy and Mines, QUEST (Quality Urban Energy Systems of Tomorrow) has experimented with various methods of bringing municipal staff from different local governments together, including webinars, facilitated peer-to-peer meetings, workshops and study tours. Facilitating this group has allowed for an identification of trends in the barriers and opportunities faced by municipalities with regard to climate change, but also in the effectiveness of this model in delivering benefit to the members. The use of inspiration and celebration of success has been an important success factor in affecting change. Also, the involvement of representatives from multiple departments has shown that everyone has valuable experience to share, and increased engagement and knowledge transfer.
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 | 0,002 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,017 | 0,001 |
| Communication savante | 0,003 | 0,001 |
| Science ouverte | 0,001 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,016 | 0,002 |
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 ».