Parental perceived immigration threat and children’s mental health, self-regulation and executive functioning in pre-Kindergarten.
Bibliographic record
Abstract
Many children in immigrant households endure unique stressors shaped by national, state, and local immigration policies and enforcement activity in the United States. Qualitative studies find that during times of heightened immigration enforcement, children as young as 3 years of age show signs of behavioral distress related to national anti-immigrant sentiment and the possibility of losing a parent. Using multiple sources of data from 168 racially and ethnically diverse families of children in pre-Kindergarten, the present study examined variability in perceived levels of immigration enforcement threat by parental immigrant status and ethnicity. This study examined associations between immigration enforcement threat and child mental health, self-regulation, and executive functioning and whether parent immigrant status or child gender moderates these associations. We found substantial variability in perceived immigration threat, with immigrant parents and Latinx parents reporting significantly greater levels of immigration threat compared to nonimmigrant parents and non-Latinx parents. Immigration enforcement threat was associated with greater child separation anxiety and overanxious behaviors, and lower self-regulation among boys and girls and among children of immigrant and U.S.-born parents. In contrast to our hypothesis, immigration enforcement threat was associated with higher self-regulation according to independent assessor ratings. Educators and healthcare providers working with young children from immigrant and Latinx households should be aware of the disproportionate stress experienced by immigrant and Latinx families due to a xenophobic sociopolitical climate marked by heightened immigration enforcement threat and racist, anti-immigrant rhetoric. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".