Development of the National Environmental Sustainability and Technology Tool (NESTT) : a sustainability measurement and management platform for Canadian egg farmers
Notice bibliographique
Résumé
The global agri-food system is necessarily central to contemporary sustainability discourse due to its significant contribution to major environmental issues and livestock-based food production is particularly impactful and considered among the top three contributors to most serious global environmental issues. As a result, there is growing consumer and regulatory demand for better sustainability measurement and management capabilities in the agri-food sector. Farm-level sustainability decision support tools characterized by their ease of access, simplified sustainability assessment models, and emphasis on effective communication and aesthetic appeal are particularly salient in this context. The dissertation research reported herein culminated in the development of a tool with such characteristics – the National Environmental Sustainability and Technology Tool (NESTT) – which was developed for the Canadian egg industry. NESTT can help Canadian egg farmers measure their farm’s environmental impacts, evaluate the mitigation potential of sustainability technologies and strategies, benchmark their performance against industry standards, and track their performance over time. The sustainability assessment framework in NESTT was based on Life Cycle Assessment (LCA). A new allocation method based on metabolic energy partitioning in hens was developed to address multifunctionality (a major methodological consideration in LCAs) in NESTT in way that is compliant with the natural science basis and requirements of the ISO 14044 standard for LCA. For measuring impacts, a modular approach based on multi-level aggregation of life cycle impacts across six modules – pullets, feed, energy inputs, water, manure management, and transportation – was implemented. To ensure that NESTT meets the requirements of farmers, a participatory design approach involving surveys and interviews of egg farmers was employed. Improvements related to user-centeredness, aesthetic appeal, and accessibility were achieved and long-term strategic options such as integrating economic assessments and adding more customized decision support features were identified in consultation with farmers. In support of these long-term goals, a preliminary economic assessment framework was also developed and integration of Multi Criteria Decision Analysis (MCDA) methods with LCA for customized decision support was explored. Overall, NESTT provides a unique, first of its kind tool to provide farmers with multi-criteria, LCA-based assessment capabilities in both Canada and the egg sector globally.
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 | 0,008 | 0,017 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,007 | 0,006 |
| Études des sciences et des technologies | 0,004 | 0,001 |
| Communication savante | 0,005 | 0,004 |
| Science ouverte | 0,002 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,014 | 0,004 |
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 ».