TURNING POINTS AND TRANSITIONS: THE ROLE OF FAMILY IN WOMEN’S IMMIGRATION EXPERIENCES
Bibliographic record
Abstract
Given the significant number of immigrants in the United States, especially immigrant families with young children, there is a need to better understand the experiences of immigrant women, and especially immigrant mothers. In particular, the factors impacting women’s decisions to migrate, migration journeys, and post-migration adjustment should be examined. Framed in family life course theory and using ethnographic, in-depth interviews, we explored these three immigration phases for 40 first-generation Latina and African immigrant women who experienced motherhood in the U.S. Results of the study expand the literature focused on immigration experiences by considering turning points and transitions in women’s migration processes, as they are shaped by both micro- (family) and macro- (socio-historical) level factors. The findings illustrate the spontaneous nature of some decisions to migrate, as well as how immigration journeys are influenced by the financial and physical supports of families and the status of their documentation. In addition, study findings point to motherhood as an important turning point for first-generation immigrant women in their adjustment to life in the U.S., and particularly in their planning with respect to staying long term. Implications for programs, policy, and future research are discussed.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.008 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 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".