Long Distance International Caregiving to Elderly Parents Left Behind: a Case of Nigerian Adult Children Immigrants in Usa
Bibliographic record
Abstract
The intent of this qualitative, grounded theory study was to understand why the Nigerian (Igbo) adult immigrants in the United States provide long distance international caregiving to their elderly parents left behind in Nigeria, the challenges they encounter, and their views on long-term service care. This study was grounded in semi-structured interviews of 20 Igbo adult immigrants residing in the Dallas/Fort Worth Metropolis. Analysis of the literature demonstrates a lack of existent topic on long distance international caregiving to elderly parents left behind in Nigeria. Findings show that reasons for Igbo adult children immigrants providing care to their elderly parents left behind stem from filial obligation, immigrant’s position in the family, perceived vulnerability of parents, and lack of government support. Also because of cultural expectations, the participants felt obligated to reciprocate to the care their elderly parents gave to them when they were growing up. While providing long distance international care, the participants encountered some challenges like adjusting to their new country, distance, financial constraints, being available for family procreation, issues with means of communication, and legal papers and parental adjustment to life in the U.S. This study also revealed that the participants would support the Nigerian government and private sector to provide long-term service care for the aging population. The findings led to some policy recommendations.
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 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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".