Envisioning Ontario’s Food and Organic Waste Disposal Ban: A Comparative Case Analysis
Notice bibliographique
Résumé
Roughly one-third, or 1.3 billion tonnes of edible food produced for human consumption is wasted around the world each year (Gustavsson et al., 2011). The production of food that is ultimately thrown away creates and exacerbates a host of economic, environmental, and social issues, including those related to greenhouse gas emissions, climate change, the depletion of finite resources, and food insecurity. Government, industry, and researchers around the world continue to assess the scope and cause of food waste, and investigate solutions through technology, regulation, and public outreach campaigns. In 2015, almost 3.7 million tonnes of food waste (including foods that could have been eaten and unavoidable waste such as vegetable peels) was generated in Ontario alone, and about 60 per cent of this waste was sent to landfill (Ministry of the Environment and Climate Change, 2018a). In 2017, Ontario put forward the Food and Organic Waste Framework, which contains an action plan and policy statement identifying how the province will address food waste within its borders. Within the Framework, Ontario states that a food and organic waste disposal ban regulation will be developed and implemented under the Environmental Protection Act, which will prohibit organic waste from ending up in disposal sites. This paper seeks to look at other jurisdictions in Canada that have implemented organic waste disposal bans in order to identify what these experiences can offer Ontario before implementing its own strategy. The key recommendation articulated throughout this paper is that food waste should be prevented above all other options, as it will have the greatest environmental, economic, and social benefits. This aligns with the frameworks guiding this research, including agroecology, the circular economy, and waste management hierarchy, and also fits within Ontario’s Food Hierarchy (which will be discussed later in this paper). Food waste prevention can be best achieved by facilitating coordination across the value chain (Gooch, Felfel, & Marenick, 2010). Ontario can support value chain coordination by funding research, reviewing existing regulations and programmes, and engaging with value chain stakeholders. Food waste prevention efforts would also benefit from developing programmes that shift behaviours at the household level, though this is secondary to value chain coordination. If food waste cannot be prevented, this paper offers recommendations for how recovered resources should be optimized in order of importance from (1) feeding people, (2) feeding livestock, and then (3) promoting soil health. These recommendations include additions and adjustments to existing regulations, legislations, and government-funded programmes, the use of tipping fees, reducing plastic contamination in the organic waste stream, and working with the agricultural community to ensure that compost meets their needs and is actively utilized by the industry to foster a viable end market.
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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 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,005 |
| Études des sciences et des technologies | 0,011 | 0,003 |
| Communication savante | 0,004 | 0,002 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 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 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 ».