Pourquoi ce travail est dans la base
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Notice bibliographique
Résumé
w h a t y o u t h I n k o f a S h I P -h o P .I am a white, Canadian woman, who at the time of this study had recently moved to the United States to take up an academic position at a private research-intensive college.And neither is Tim. 1 Also white, he is a high school language arts teacher, a haiku poet, runner, and committed bird-watcher who self-admittedly knew nothing about rap music.This disjunction helps explain his students' surprise when Tim announced that the class would be studying hip-hop and spoken word culture in the last term of their senior year.Then he introduced me as the professor who would be coteaching the class.One student asked if he could borrow a tape-recorder, since "there's a lot going on in the school teachers don't know about," a situation he was hoping to change.The "lot" he referred to is the hip-hop poetry, including individual and group (or cipher) improvised freestyling and rapping, which pervades the hallways of urban high schools across the United States but is rarely invited into classrooms.Which doesn't mean that popular culture, and in this case hip-hop, isn't already present in schools, shaping the identities of students and therefore how, what, and why they learn.Tim teaches English, specializing in creative writing, in an urban arts magnet high school in a midsized city in the northeastern United States.In the fall of 2001, I was an assistant professor in a local university's faculty of education.The university suffers from the elitist reputation problems of similar private institutions located in poor urban centers.I had been studying, in theory, the implications of spoken word and hip-hop culture for youth identities and language practices.I met Tim, and he asked me to help him develop and teach a curriculum grounded in hip-hop culture in two of his senior classes.He had been teaching English and creative writing in the city school district for more than twenty years and felt that his ignorance about
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.
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 | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 découle