MétaCan
Menu
Retour à la cohorte
Enregistrement W1593571217

Five Blackfoot Lullabies

2011· article· en· W1593571217 sur OpenAlexaboutno aff
Mizuki Miyashita

Notice bibliographique

RevueProceedings of the American Philosophical Society: Held at Philadelphia for Promoting Useful Knowledge · 2011
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueLinguistic Variation and Morphology
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésLyricsLinguisticsIndigenousSection (typography)MainstreamSubject (documents)MusicalPhonologyHistoryEthnomusicologySociologyPsychologyLiteratureArtComputer sciencePhilosophy
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

THE TOPIC OF LANGUAGE and music has interested scholars of various research fields. Some scholars in musicological literature strive to apply linguistic theory to musical analysis (e.g., Feld 1974; Feld and Fox 1994; Netti 1958), and cognitive studies show how similarly the human brain processes music and language (Patel 1998, 2003). This interdisciplinary subject, however, has not received significant attention in mainstream linguistics. A few linguists, including Hayes and MacEachern (1996, 1998), Hinton (1984), and Fitzgerald (1998), provide linguistic analysis of folksongs or indigenous songs, but a common aspect of linguistic analyses of folk verses in general is that they are based on songs that are well known, if not already documented. Indigenous songs are not only rarely documented, but they are also documented mostly by ethnomusicologists. Because of this, the music itself is well recognized, but recording and analysis of lyrics tend to be understudied. When lyrics and their linguistically important information such as morphosyntax and phonology are documented, the opportunities for folksong study can be significantly expanded. This paper provides preliminary analysis of five Blackfoot lullabies as the first step toward a full account of Blackfoot lullabies. The organization of the paper is as follows. In section 1, 1 briefly outline the background of the Blackfoot language, choice of song type, Blackfoot song collections, Native American folksong study, and the fieldwork process. In section 2, 1 describe lyrics, utilizing English translation. In section 3, a brief discussion of the characteristics of the songs is provided. In section 4, I discuss the relationship between the metrics of language and songs.1 BACKGROUND1.1 LanguageBlackfoot is an Algonquian language spoken in Alberta, Canada, and northwestern Montana, United States. There is one tribal group in the United States, Aamsskapipikani (Southern Piegan), and there are three in Canada: Siksika (Blackfoot), Kainai (Blood), and Aapatohsipikani (Northern Piegan). There are dialectal variations among these groups (Frantz and Russell 1995). The present study is based on the dialect spoken by the Southern Piegan tribe, which resides on the Blackfeet Reservation in Montana.2 As is the case with other indigenous languages, the number of native Blackfoot speakers drastically decreases every year. The United States Census of 2000 shows that the population of Blackfoot speakers in Glacier County, Montana, is approximately 1,450 people. According to a survey conducted by the Piegan Institute, however, the situation is more dire. They estimated the number of proficient speakers at 100, and these speakers are seventy-five years old or older (Darreil Kipp p.c.).3 In addition, the Piegan Institute's study found that the proficiency of self-claiming Blackfoot speakers varies significantly. As a clear indication of such language decline, Blackfoot lullabies are no longer sung to infants. I hope that my work here will be used not only by linguists and ethnomusicologists, but also by teachers and parents of the Blackfeet Reservation to enhance native knowledge of Blackfoot language and culture.1.2 Choice of Song TypeMost American Indian songs I came across in various forms, such as recordings of powwow songs, had abundant vocables with few if any meaningful words. Vocables are nonsense words sung along with the melodies. These powwow songs are exchanged and sung by members of different tribes regardless of the similarity in linguistic traditions between the tribes. However, linguistic study is best conducted on songs that have lyrics with recognizable words; for this reason, I looked for songs that were not subject to cross-tribal exchanges. If songs are not exchanged cross-tribally and stay within the same social-linguistic group, lyrics can keep their original, meaningful forms. Such songs may be those that are sung to children. Among children's songs, lullabies are sung to infants being raised as members of the society, and they are not likely to be shared beyond a linguistic community. …

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 distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,003
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Études des sciences et des technologies
Catégories consensuellesÉtudes des sciences et des technologies
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: Théorique ou conceptuel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,271
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,003
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0000,001
Études des sciences et des technologies0,0020,003
Communication savante0,0000,000
Science ouverte0,0010,001
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,056
Tête enseignante GPT0,311
Écart entre enseignants0,256 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeThéorique ou conceptuel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2011
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueProceedings of the American Philosophical Society: Held at Philadelphia for Promoting Useful KnowledgeMême sujetLinguistic Variation and MorphologyTravaux en français237 207