Reallocation of Space for Outdoor Dining: An Analysis of COVID-19 Pandemic Outdoor Dining Policies and Perceptions in Ontario
Notice bibliographique
Résumé
In recent years, the COVID-19 pandemic created disruptions in the restaurant industry. Consequently, cities in Ontario developed pandemic-induced patio policy with the goal of allowing restaurants to continue operation under lockdown restrictions. Pandemic-induced patio policy was identified to have the potential to contribute to long-term changes in these areas. Despite the increase in policy development, there is a gap in literature when considering how Ontario cities developed their policies and what the dominant themes of these policies are. Through a qualitative, mixed methods approach this thesis explores the changes that were made to patio policy in Ontario during the COVID-19 lockdowns of 2020 and 2021. The first manuscript assesses the extent that pandemic-induced patio policy was developed in the 52 cities in Ontario and what the key features of these policies were. The second manuscript explores how changes to patio policy were perceived by participants in the food retail environment. The first study concludes that supporting restaurant businesses through patio policy development was heavily prioritized by cities in Ontario during the COVID-19 pandemic. These policies varied in terms of time frame and method of implementation. Major policy themes included financial incentives, changes to the application process, and development of city-specific policy features including road closures, as well as other programming including promotional programs. A total of 10% of cities in Ontario implemented elements of their new patio policies post-lockdowns. Additionally, these policies were exempt from public consultation requirements, however some cities chose to conduct community engagement. The second study concluded that patio policy was a prevalent topic for employers, employees, and stakeholders when discussing responses to the COVID-19 pandemic. Themes discussed in interviews varied between the interview groups. Of the different respondent groups, employers discussed patios and patio policy most frequently. They found patios policy to be supportive, and that patio dining during the pandemic contributed to profitability. For some employees, patios lead to concerns over safety and create negative workplace environments. The feasibility of patio policy was perceived to be influenced by factors including vehicle use on the street, availability of patio space, and the business’s financial situation. Recommendations based on the findings are associated with developing patio policy in a holistic manner, which considers compatibility with current streetscape functions and relevant plans.
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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 | 0,002 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,003 |
| Études des sciences et des technologies | 0,009 | 0,004 |
| Communication savante | 0,003 | 0,001 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».