Soundhikes and Oral Histories from Appalachian Protected Lands: Implications for Equitability and Access
Notice bibliographique
Résumé
In the 1960s and 1970s, Canadian music educator R. Murray Schafer developed the field of soundscape studies, later introducing the “soundwalk”: an empirical method for identifying a soundscape and its components through the activities of walking and close listening. Human activity in a soundscape, or a soundwalk, is known as anthropophony: a category of sounds produced by humans, including language, vocalizations, and musics. In this individual oral presentation, the primary researcher will share her experiences in creating a framework for her Master’s in Appalachian Studies Applied Project at East Tennessee State University. The soundwalk method will be adapted into a series of recorded “soundhikes.” During these hikes, the primary researcher and her participants will engage in a series of interviews in areas designated as state parks and national forests in the Upstate of South Carolina. These oral histories (with English-language translations, when applicable) will be submitted to the Archives of Appalachia, and will be used in the primary researcher’s ongoing research on Appalachian representation in the region’s protected spaces. As these protected spaces have reached nearly one hundred years of existence as “state parks” or “national forests”, the demographics of the people visiting them have changed drastically. The lenses of Critical Race Theory and Feminist Disability Theory will be used to explore these new demographic realties, and to advocate for resources benefitting those who have self-reported any of the following while attempting to enjoy Appalachian nature spaces: barriers to access, feelings of fear, or experiences of rejection. The ultimate goal of the oral history soundhike project, influenced by the principles of Public Sphere Theory, is to feature present-day voices which have not been historically included in Appalachian “nature narratives,” leading to increased representation in the field of Appalachian Studies. Though data collection has not yet begun, it is the hope of the primary researcher that this information will have a pragmatic application. Applicable portions of this project will be submitted to agencies, located in South Carolina’s Upstate region, which have indicated an interest in attracting more diverse stakeholders. The finished project will advocate for more diverse language and cultural resources and programming in protected nature spaces.
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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) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 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) | 0,000 | 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 ».