Mapping the underground soundscape : fieldwork among the subway musicians of Toronto
Notice bibliographique
Résumé
The term soundscape was developed by R. Murray Schafer to describe "the sonic environment" (Schafer, 1977, p. 274), which encompasses all the sounds that surround us; his studies of urban soundscapes are particularly noteworthy. One soundscape that has been rarely studied is one that is found in many urban centres - the subway. "Mapping the Underground Soundscape" is six-year musical ethnography exploring the Toronto Transit Commission's (TTC) Subway Musicians' Programme and how it provides a unique auditory environment in its stations, passageways, platforms, and thoroughfares. More broadly, this thesis examines the relationship between music and the urban environment. It considers the influence of music on an urban environment (the subway) and how that environment is imagined and represented, and then how that urban environment influences music-making practices. Just like landscapes, soundscapes have a figure-ground relationship. At what point does the music become the figure? If one listens closely, one can hear sounds emanating from a guitar, an erhu, a violin, or keyboards, sounds, perhaps on a first hearing, uncharacteristic of the subway. Through the continual shift of figure and ground of these subway musical performances, the transit system becomes a temporary performance space for those willing to listen. This figure-ground test prompts two questions: What can we experience in an urban space just by listening? And how do we navigate a route through that world of sound to reach a greater understanding of it whilst also, literally, negotiating our movements through that urban space? The evidence suggests that the TTC Subway Musicians' Programme offers a microcosm of Toronto society. Thus, this underground soundscape can be used to explore IV and identify facets of the city's musical identity and the lives of its inhabitants. Such a study can also offer a new perspectives on how civic environments become established through policy and management schemes which champion the installation of music into urban environments once devoid of music cultures, that is, organised, identifiable sounds, crafted sounds that carry meaning, that are able to lift commuters out of an otherwise auditory jungle (a world of noise with only coded information: the train is now arriving, the doors opening and then closing, I am now leaving the station and getting to my destination). Thus, it is clear that the TTC system is highly complex in terms of its community and cultural relations and its political economy. Moreover, the interweaving of strolls, sound maps, sound clips, sound exercises, and photos within the text, allows for greater opportunity to experience and explore the underground soundscape at specific points in time. Ultimately, this thesis, which one might regard as a sonic mapping of the underground through sound, brings popular music-making and urban geography into soundscape analysis, highlights the role of music in placemaking, and presents a new way of navigating the city.
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 | 0,002 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,002 | 0,004 |
| Études des sciences et des technologies | 0,016 | 0,009 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».