Feeling Safe While Having Fun? Review of Experienced Safety and Fear of Crime at Events and Festivals
Notice bibliographique
Résumé
Abstract Events and festivals are big business. Despite differences, the overall goal of providing visitors with a positive experience and making a profit for the organization of the event or festival is the same. As clear liminal settings, events and festivals trigger the experience of freedom among visitors, but research also indicates that this comes at a price of heightened risk of, for example, ‘(...) pickpockets, sexual assault, and terrorist attacks (...)’ (Hoover et al., The Canadian Geographer/Le Géographe canadien 66:202, 2022). At the same time, there is little research attention for how such risks of crime victimization are experienced, and how safe people feel at events and festivals more generally. This is somewhat surprising because, in general, safety is considered to be crucial to the success of (semi)public spaces and people’s willingness to frequent these. One could hypothesize a similar importance to event and festival settings (Dewilde et al. Journal of Peace Education 18:163–181, 2021) and some authors (Pivac et al. Journal of the Geographical Institute “Jovan Cvijić” SASA 69:123–134, 2019; Barker et al., Journal of Travel Research 41:355–361, 2003) claim the experience of safety to be crucial for the future of events. In this chapter we will explore what is special and (potentially) unsafe about events and festivals and review what is known about event and festival visitors’ fear of crime and explanatory factors. Findings are contrasted with knowledge from the general fear of crime literature. In doing so, we pay special attention to gender differences in the experience of fear of crime at events and festivals, the role of environmental factors, and the role of surveillance and policing. Based on our exposition, it follows that there clearly is no one-size-fits-all solution for the prevention of fear of crime at events and festivals, and a practical approach has to be based on tailor-made analyses for specific events and festivals. Increased security and surveillance are not per se the answer to fear of crime at events and festivals; in particular circumstances these might even alarm visitors about the risks of crime victimization, affecting their experienced safety in a negative way. It can also be questioned to what extent such an approach is sensitive to recognizing and addressing the (perceived) threat of sexual harassment and violence, which the literature we reviewed consistently conveys as a specific and pressing risk at events and festivals, especially to women. A way forward could be raising awareness of sexual violence and harassment among visitors, staff, and organizers of events and festivals. We would also argue monitoring perceived risk of different types of victimization (among which sexual harassment and violence) could be expanded using different techniques, such as app-based measurements of real-time experience of safety. In general, it seems that the prevention of fear of crime at events and festivals needs a bottom-up, tailor-made approach, in which technological solutions may play a role but should not be considered a one-size-fix-all.
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 | 0,005 | 0,023 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,001 |
| Bibliométrie | 0,008 | 0,008 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,003 | 0,004 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
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 ».