Immigrant households and hardships after welfare reform: a case study of the Miami‐Dade Haitian community
Bibliographic record
Abstract
Compared with other nations such as Canada and Australia, the US experiment with welfare reform has yielded steeper and more immediate caseload declines. These declines have been especially pronounced for immigrants who have been subject to a new set of service restrictions implemented under the 1996 Welfare Reform Act. This article examines service access for Haitian immigrants in Miami, Florida since the onset of these reforms. The data presented here are derived from a series of qualitative interviews with Haitian service professionals and a quantitative survey of Haitian immigrant households. The survey data indicate that many Haitians who are living in poverty and qualified to access services are not enrolled for government services. Confusion over eligibility guidelines explains some of the variation of these low enrolments for specific services (such as child health insurance and childcare) but not for services most commonly used by immigrant adults such as food stamps and Medicaid. The survey also demonstrates that qualified immigrants living in households with unqualified persons are less likely to access services than are other qualified immigrants and are more likely to experience hardships that impede their ability to find stable employment. The concluding discussion highlights the significance of using a household unit of measure in assessing immigrant enrolments and hardships.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.017 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".