Bibliographic record
Abstract
Abstract With rising rates of immigration around the globe we have seen increased interest in the socioeconomic situation of immigrants as well as their health status and health care needs, and their impact on the host countries' health care system. Much of the research has focused on immigrants of non‐Western origin to the three traditional immigration destinations—the United States, Canada, and Australia. While earlier research was often focused on the negative impact of immigration on immigrants' health and mental health, research in the last couple decades has consistently found evidence of relatively good health among most immigrants especially “voluntary” immigrants from non‐Western origins to western nations, a finding often referred to as an immigrant health paradox . Most interest in immigrant health in the United States has focused primarily on immigrants from Latin America, especially Mexico. Immigrants tend to have better health and mortality profiles than the native born, especially from the same racial/ethnic group. While there are some exceptions to these findings, which we note in the current entry, the preponderance of evidence indicates that selection processes are pivotal for understanding the paradox. Sociocultural resources have also been implicated; however, most of this line of research is still underdeveloped. In the current investigation we outline (a) foundational research, (b) cutting edge research, and (c) key issues for future research. We argue that better health among immigrants is not necessarily paradoxical. Most “voluntary” immigrants arrive in their country of destination with good health and a positive outlook on life. However, the finding that longer stays in the United States deplete health likely reflects acculturation forces. More research is needed to more adequately capture acculturative stress processes, changes in lifestyle factors (smoking, diet, and exercise), and the sociocultural resources that protect immigrants from being vulnerable to premature mortality.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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 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".