MétaCan
Menu
Retour à la cohorte
Enregistrement W7022258463

Partis, Michael

2007· article· en· W7022258463 sur OpenAlexaboutno aff

Notice bibliographique

RevueFordham Research Commons (Fordham University) · 2007
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueCrime, Illicit Activities, and Governance
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésWifeApartmentGrandparentWorking classQuarter (Canadian coin)
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Michael’s grandmother came to New York in 1972. She was originally born in Honduras, and then moved to Belize. From there she moved to L.A and then finally settled in New York. Michael’s Grandmother is Garifuna. His mother was born in Belize and moved with his grandmother to the Bronx, where she met his father. His father was originally from Brooklyn and moved to the Bronx because of a disagreement he had with his family. When his parents met they were in their early 20’s. Growing up he barely saw his father.\nHe grew up on 165th and Bryant Avenue. His early memories of his neighborhood involved working class families followed by drugs. Most of the families in his neighborhood were black and only a few were Latino. He believes the reason drugs hold such a predominant place in his memory is because his mother was an addict. Because of his mother’s drug problem, she was never that involved in his caretaking. He claims his grandmother raised him, not his mother. In addition to his mother, however, he does remember his neighborhood as having a drug problem. His block had many apartment buildings, a school, and a park on it. He spent a lot of time in this park when he was growing up. He does not remember too many fathers in his neighborhood. Most of the men in the neighborhood were involved with drugs, either dealing or using. Because of this, he and the other boys in the neighborhood found this lifestyle appealing.\nHis mother’s drug use was very serious. When he was younger, his mother would often disappear for days and was using drugs heavily. However, she was able to do some work and when he was 10, he and his mother moved to the Castle Hill Projects. While living there, his mother would have relapses and use drugs again. Surprisingly, she was able to work at this time. When he was 12, his mother was murdered.\nAs he got older, he experienced more violence and more of the gang culture. Halloween became a scary time of year, not because of the costumes, but because of the violence that came along with it.\nThough he had a traumatic home life, fortunately school came naturally to him. His teachers recognized his gifts from a very early age. When he was young, he really enjoyed reading. He went to St. John’s elementary school. He got into trouble there because he would try and alter his uniform. Even though he was defiant, he still did well in school. He did so well, in fact, that he received a scholarship to go to a Catholic High School. In high school dress became more important. Although they still had to wear a uniform, shoes became a way a student could add their individual style to it. He describes how many would blow their entire summer’s pay on a pay of shoes to wear to school. After high school, he attended Fordham University.\nWhen he was younger, he listened to country music because this was the music his grandmother enjoyed. His mother, however, was more into R & B and hip-hop. One of the first hip-hop groups he liked was Wu-Tang Clan. He remembers the predominance of boom boxes and batteries. People would play their music when they were doing anything, from playing basketball to sitting on a bench. He was drawn to hip-hop because of the lyrics, which really touched him. He really enjoyed reading The Source, which he began reading in 1995. When he was in 8th grade, he saw his first emcee battle. When he was in the 7th grade, he was first exposed to mix tapes. He got them from the street and the content was mostly bootlegged.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,002
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Autre · Signal consensuel: Autre
Score de désaccord entre enseignants0,417
Score d'incertitude au seuil0,832

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,002
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0060,001
Communication savante0,0040,003
Science ouverte0,0010,003
Intégrité de la recherche0,0020,003
Charge utile insuffisante (le modèle a refusé de juger)0,4170,155

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 Opus0,108
Tête enseignante GPT0,387
Écart entre enseignants0,280 · 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; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreAutre

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

En bref

Citations0
Publié2007
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueFordham Research Commons (Fordham University)Même sujetCrime, Illicit Activities, and GovernanceTravaux en français237 207