Care For America’s Elderly And Disabled People Relies On Immigrant Labor
Bibliographic record
Abstract
As the US wrestles with immigration policy and caring for an aging population, data on immigrants' role as health care and long-term care workers can inform both debates. Previous studies have examined immigrants' role as health care and direct care workers (nursing, home health, and personal care aides) but not that of immigrants hired by private households or nonmedical facilities such as senior housing to assist elderly and disabled people or unauthorized immigrants' role in providing these services. Using nationally representative data, we found that in 2017 immigrants accounted for 18.2 percent of health care workers and 23.5 percent of formal and nonformal long-term care sector workers. More than one-quarter (27.5 percent) of direct care workers and 30.3 percent of nursing home housekeeping and maintenance workers were immigrants. Although legal noncitizen immigrants accounted for 5.2 percent of the US population, they made up 9.0 percent of direct care workers. Naturalized citizens, 6.8 percent of the US population, accounted for 13.9 percent of direct care workers. In light of the current and projected shortage of health care and direct care workers, our finding that immigrants fill a disproportionate share of such jobs suggests that policies curtailing immigration will likely compromise the availability of care for elderly and disabled Americans.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".