Aging Filipina migrants’ experiences of transnational end-of-life care and loss over time
Bibliographic record
Abstract
This article addresses experiences of transnational end-of-life care among aging Filipina migrants before and during COVID-19. de Leon addresses the emotional costs associated with loving and losing kin from a distance both before and during the pandemic, drawing on their autobiographical account of distant care by proxy during their aunt’s wake and funeral. Blower-Nassiri highlights the exacerbated fears and anxieties around dying, illness, and end-of-life among aging migrants, drawing on two life histories of retired nurses who recalled moments of loss and being absent for end-of-life events, such as funerals, before and during the pandemic. Together, de Leon and Blower-Nassiri provide an intimate portrait of three Filipina migrants’ experiences with end-of-life care and loss. They further address the limitations of the life course framework in their consideration of how care carries on, across generations through end-of-life practices and rituals that signal an accrual of loss over time.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".