Four Commentaries: Looking to the Future
Bibliographic record
Abstract
To provide an array of perspectives about policies needed to serve the growing number of children of immigrant families in our country, we asked experts across various organizations and backgrounds to respond to this question: How should policymakers, advocates, stakeholders, and practitioners respond strategically and proactively to demographic change and increasing diversity in order to promote the healthy development, productivity, and well-being of our nation's children into the future? Their responses follow. COMMENTARY 1 Mark Greenberg and Hedieh Rahmanou The United States is in the midst of a profound demographic shift, to which our workforce and family support policies have not yet adequately responded. Almost one-fifth of the nation's children, and one-quarter of the nation's low-income children, are now immigrants or the children of immigrants. (1) One-fifth of the nation's low-wage workforce is comprised of immigrants, and half of the nation's job growth during the 1990s was attributable to immigrants. (2) Any national strategy for reducing child poverty, promoting child well-being, and helping low-wage workers advance must address the needs and circumstances of immigrants and their children. Federal policy has largely taken the opposite approach. In 1996, Congress elected to restrict access to food assistance, health care, income support, employment services, and other benefits and services for legal immigrants. Since that time, there have been limited partial repeals of some, but not most, of the restrictions. The result has been curtailed eligibility, a patchwork of uneven state and local responses, and sharp drops in participation among families that could benefit from services and assistance. As the articles in this issue and other analyses make clear, children of immigrants are likely to suffer significantly greater hardships than children of U.S.-born parents, and they are less likely to be receiving public benefits that could reduce their hardships and enhance their well-being. Moreover, the nation's workforce policies deny immigrant parents the assistance that might help them advance beyond the low-wage labor market. This commentary summarizes some of the key data suggesting the magnitude of the problem, and proposes a set of policies that could enhance the well-being of this significant and growing share of the nation's children. Income, Poverty, and Hardship among Immigrant Families In 2002, about 19% of the nation's children and roughly one-quarter (26%) of the nation's low-income children (with family incomes below 200% of poverty) were children of immigrants. (3) The poverty rate among children of immigrants was 22%, compared with 14% for children of U.S.-born parents. Most children of immigrants (51%) live in families with incomes below 200% of poverty. As detailed by Hernandez in this journal issue, on virtually every measure of hardship, children in immigrant families fare less well than children in families of U.S.-born parents. For example, children of immigrants are more than four times as likely to live in crowded housing and nearly twice as likely to be uninsured. They are more likely to have poorer health, and to live in families worried about affording food. (4) At the same time, low-income immigrant families are more likely to contain a worker than are low-income families with parents born in the United States. As explained by Nightingale and Fix in this journal issue, the fundamental difficulty faced by low-income immigrant families is not unemployment but low wages, substantially attributable to limited language proficiency and education. In 2002, nearly half (48%) of foreign-born workers were low-wage workers. (5) Among these low-wage workers, most (62%) were limited English proficient, and nearly half (45%) had not completed high school. Legal status is a significant issue for some, but most low-wage foreign-born workers in the United States are here lawfully. …
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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 | 0.018 | 0.096 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.010 |
| Scholarly communication | 0.009 | 0.018 |
| Open science | 0.007 | 0.007 |
| Research integrity | 0.057 | 0.063 |
| Insufficient payload (model declined to judge) | 0.021 | 0.005 |
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".