Risks & Responsibilities: The Complexities of Enabling Safety & Harm Reduction at Music Festivals
Notice bibliographique
Résumé
The purpose of this thesis is to examine the risks and subsequent harm reduction strategies that occur at music festivals with a focus on Western Canada. Music festivals are liminal spaces that form temporary communities in bounded locations, and as such are sites that see decreased inhibitions and increased risks. Using critical-interpretive medical anthropology as the framework, these risks are analyzed and grouped based on their impact − risks to the individual body, physically and mentally, and risks to the community as a whole. Instead of looking at each risk in isolation, a holistic approach in this context specifically is essential due to the interrelated and compounding nature of these potential harms. This framework also provides the basis for the second half of this thesis, which interrogates the entangled and often contradicting responsibilities at play for mitigating these risks.\n\nUsing a rapid ethnographic research design, three music festivals were chosen as the field sites for this research, with each festival located in a different province (British Columbia, Alberta, Saskatchewan) to allow for comparative policy analysis. This comparison helped to illuminate just how varied the experiences at different festivals can be. There is largely no formal regulation on risk mitigation at mass gathering events such as music festivals, outside of fire or alcohol safety. This absence forces festival organizers to engage with the securitization of habitat, as per Nikolas Rose, resulting in different harm reduction strategies and risk priorities at each event. In turn, through governmentality, many patrons have internalized responsibility for both themselves and those around them. Additionally, festivals and governments with prohibitionist stances on drug use, rather than harm reduction grounded in prevention and realism, are unintentionally contributing to more dangerous risk behaviours. My research demonstrates that all the different parties involved − individuals, communities, organizers, and governments − need to communicate and be on the same page in order to create and enable sustainable safety at music festivals. This is currently not the case in Canada, where criminalization and enforcement are still fundamental structures hindering harm reduction, contributing to the escalating risks created by the unregulated drug market.
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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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,029 | 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 ».