An Autoethnography on Intergenerational Relationships and Transnational Care for Older Parents
Bibliographic record
Abstract
I employ autoethnography to undertake a broader scholarly inquiry on intergenerational relationships and transnational care shaped by global migration and aging. Specifically, I reflect on the dynamics of my relationship with my mother, beginning with my departure from my home and spanning a period of 40 years, 8 in China and 34 outside China. In doing so, I contemplate theoretical models of intergenerational solidarity, ambivalence, and role ambiguity. I also challenge cultural assumptions of filial piety. The geographical distance, passage of time, and acculturation process have profoundly influenced my perception of filial piety, which differs markedly from my mother’s. However, this divergence in consensual solidarity—marked by variations in attitudes, beliefs, and values—does not translate into weakened affectual solidarity, characterized by positive sentiments and emotions. Furthermore, aided by advancements in transportation and social media technology, I have been able to extend crucial emotional and some “instrumental” care to my mother, along with financial support if needed, despite limited hands-on care. Nevertheless, I must negotiate my care for my mother and navigate a delicate balance in coordinating my care efforts with those of my non-migrant siblings.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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".