‘You're Good with your Hands, Why Don't You Become an Auto Mechanic’: Neighborhood Context, Institutions and Career Development
Bibliographic record
Abstract
Previous research has linked sociodemographic neighborhood characteristics with labor market outcomes for youth, but this research has provided little evidence of how these linkages work. In this article I examine practices of urban institutions and the career development of inner‐city minority youth in the United States. A comparative study of two Latino inner‐city neighborhoods in San Antonio, Texas, analyzes in‐depth interviews with seventeen administrative officers of community‐based institutions. The results reveal that institutional practices and administrators' interpretations of the cultural attributes of youth and neighborhoods differ between the two case study areas. In one neighborhood, cultural preconceptions among administrators, accompanied by the spatial and social isolation of youth, channel some youth towards secondary careers. Institutions in the other neighborhood focus on social and spatial integration strategies and thereby facilitate acculturation. The article explores institutional practices of cultural marginalization. Certaines recherches ont déjè lié les caractéristiques socio‐démographiques des quartiers aux débouchés du marché du travail pour les jeunes, mais elles ont apporté peu d'indications sur les modes de fonctionnement de ces liens. Cet article examine les usages d'institutions urbaines et le parcours professionnel de jeunes de minorités vivant dans des quartiers urbains déshérités aux Etats‐Unis. Une étude comparative de deux quartiers défavorisés latino‐américains de San Antonio (Texas) analyse les entretiens poussés réalisés avec dix‐sept agents administratifs d'institutions liées á la collectivité. Les résultats révélent que les usages institutionnels et les interprétations des administratifs quant aux attributs culturels de la jeunesse et des quartiers différent entre les deux zones d'étude. Dans l'une, les a priori culturels des administratifs, associés á l'isolement géographique et social des individus, canalisent les jeunes vers des carriéres de second ordre. Dans l'autre, les institutions se consacrent aux stratégies d'intégration sociale et spatiale, facilitant ainsi l'acculturation. Les pratiques institutionnelles de la marginalisation culturelle sont également examinées.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".