Influences of Engaging in a Participatory Monitoring and Evaluation Process on Stakeholder Perceptions of Key Performance Indicators for Trails
Notice bibliographique
Résumé
Trail use is growing globally. Managers confront the classic dilemma of protecting ecological integrity and providing enriching experiences. They concomitantly face the imperative for sustainability—contemporarily characterized by complexity, uncertainty, conflict, and change. Heightened levels of visitation are cause for immense concerns due to adverse impacts to the environment as well as visitor experiences. COVID-19 exacerbates these challenges as heightened levels of visitation are occurring, while managers simultaneously face decreases in conservation funding, and restrictions on protected area operations. Participatory monitoring and evaluation (PM&E) is an emerging in- novation to collaboratively address social-ecological challenges, such as issues as- sociated with trail use. This research is concerned with exploring the influences of engaging in a PM&E process on stakeholder perceptions of key performance indicators (KPIs) for trails. This study compares stakeholder perceptions of KPIs for trails before and after a PM&E workshop at the Niagara Glen Nature Reserve in Ontario, Canada. Results show that PM&E can facilitate consensus among stakeholders regarding the overall goals of management and associated KPIs for environmental management planning. Stakeholders were shown to experience a real change in their perceptions of KPIs. The PM&E process studied show that participants became more conscious of the wider social realities as well as their perceptions of trail management. The study has important implications for managers concerned with trails and sustainability, including building consensus among key stakeholders to reach management goals, enhancing localized decision making, and building capacity for management towards sustainability. Trails, as well as the wider community can ultimately benefit from participatory approaches to environmental management. Consensus-building through PM&E works to enhance decisions that account for a diversity of perspectives. Stakeholder participation in trail management increases the likelihood that local needs and priorities are met, while allowing stakeholders to build capacity and learn to effectively manage their environments. Furthermore, positive perceptions from being meaningfully involved in PM&E can ensure the support of constituents, which is imperative for the long-term success of management planning.
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 | 0,002 | 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 ».