How Positive Youth Development Can Support Low-Income Roma Youth Living in the United States
Bibliographic record
Abstract
Deprivation and discrimination, including the destruction of housing settlements, forced evictions, and persistent violence, led a portion of Europe’s 12 million Roma to seek refuge in the United States and Canada. Approximately 1 million Roma live in the United States, and 80,000 Roma currently live in Canada. Profound experiences of injustice in their home countries have led Roma in the United States to keep their lives hidden from mainstream society. The Roma as a race/ethnicity is not accounted for in any American surveys, and research on their well-being in the United States is scarce. This chapter fills knowledge gaps by presenting a one-of-a-kind comprehensive literature review synthesizing empirical evidence on the lives of Roma people and their youth in the United States by applying the positive youth development (PYD) framework that focuses on promoting positive asset-building for youth and seeing youth as vital resources in development strategies. In doing so, the chapter advances beyond the more usual narrative that has focused on the problems of Roma youth to examine the mechanisms that can enable them to flourish in the United States. Romani youth is a case study example of youth of color in general; this chapter adds to the body of knowledge that examines how PYD development matters for positive developmental outcomes of a minority group that has experienced socioeconomic disparities strictly because of the stigma of their identity.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".