Predicting depressive symptoms from acculturative family distancing: A study of Taiwanese parachute kids in adulthood.
Bibliographic record
Abstract
We applied Hwang's (2006a) acculturative family distancing (AFD) theory to Taiwanese "parachute kids," who had immigrated to the United States or Canada as unaccompanied minors and remained in North American as adults. It was hypothesized that each dimension of AFD-communication breakdown and cultural value incongruence-would uniquely predict conflict with participants' family members in Taiwan, which would, in turn, predict their depressive symptoms. In a sample of 68 former parachute kids aged 18 to 36 years, the relation between communication breakdown and depressive symptoms was fully mediated by family conflict. On the other hand, the mediation effect was not found for cultural value incongruence. Moreover, a suppression effect occurred, suggesting the likelihood that an additional, unknown variable accounts for the relation between cultural value incongruence and depressive symptoms. We concluded, from these results, that the 2 AFD dimensions operate differently in this population than in previous AFD research. This conclusion was further supported by the finding that participants reported significantly more communication breakdown than cultural value incongruence with family members residing in Taiwan.
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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".