Notice bibliographique
Résumé
As Vicar of Santa Fe Episcopal Church on the south side of San Antonio, Texas in the early 1990s, my pastoral experience in this poor barrio saw an increase in incidents of alcohol and drug abuse, domestic violence, teen pregnancies, and gang violence. After breaking up a gang initiation of a young girl in the parking lot of our church, I had the opportunity to talk with some of the young girls. I mentioned to them that life could be bigger and better than sex, drugs, rock and roll, and the violence of la vida loca. They all disagreed, and said what chance did they have to make a better life? There were no jobs in San Antonio. Needless to say, I was pretty depressed that afternoon. There was truth in their perception. Several south and west side companies that paid decent wages - including the Roegelein meat packing plant, Miller Curtain, and San Antonio Shoes - had all closed their doors. Two of the largest employers, Levi Strauss and Kelly Air Force Base, the main source of middle class income for south and west side families, were closing. The perception of San Antonio's economic downturn was pervasive. Even Red McCombs, a leading businessman, barked at a meeting of business leaders, are we doing here? There are no jobs in San Antonio! San Antonio was an economy in transition. We had lost some fourteen thousand jobs in manufacturing, textiles, transportation, and other low-skill, modest-wage occupations. Santa Fe Episcopal Church was a dues-paying member of a broad-based community organization named Metro Alliance. Together with our sister organization, Communities Organized for Public Service (COPS), we were affiliated with the Industrial Areas Foundation (IAF). COPS/Metro represented over fifty congregations and ninety thousand people. In talking with other clergy, we found that a crisis was already surfacing in the same pastoral tragethes experienced at Santa Fe. Instead of merely looking to resolve the immediate concerns, we examined instead this economic downturn as a causal factor in the violence, abuse, and tragedy in our parishioners' lives. COPS/Metro embarked on a two-pronged research strategy. One looked internally at our communities, and the other looked externally to see what the job situation really was. The tried-and-true methodology of IAF community organizations is to begin with house meetings to elicit the metis or intuitive knowledge embedded in the real-life experience of our folks. What we found after hundreds of house meetings was a hard-working, loyal workforce that had a dismal experience with formal education and an even more dismal experience with educational providers that promised increased skills for higher paying jobs. Indeed, a common experience was one of incurring debt through the student loans necessary to complete their training and a nearly nonexistent track record of finding a better job. This experience of exposing their lack of education and feeling swindled by the job training proprietary schools left many with a sense of shame. It was only in trustworthy house meetings that many opened up with their stories. When they realized that they were not alone, there was a surge of anger and the passion that led to a struggle to change the labor market in San Antonio. On the other side, COPS/Metro leaders conducted nearly forty meetings with various business leaders in San Antonio to discover what their needs were as employers. What we discovered was that while San Antonio had lost fourteen thousand low-skilled jobs, it had also gained nineteen thousand jobs in higher skilled areas that also paid better. At a meeting with Callie Smith, the CEO of the Baptist Hospital system, he disclosed that he had three hundred jobs that he needed filled that very day. Indeed, virtually all the business leaders in the allied health field were desperate for nurses, radiology techs, respiratory techs - all the allied health positions. The airplane industry was looking for skilled sheet metal workers, and there were also hundreds of jobs available in electronics and technology. …
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Comment cette classification a été obtenuedéplier
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 | 0,001 | 0,002 |
| 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 | 0,001 |
| 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) | 0,003 | 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 ».