Bibliographic record
Abstract
The aim of this thesis was to explore existential loneliness from the perspective of older migrants. The phenomenon was examined through the lived experiences of both older migrants and non-migrants, as well as through the perceptions of healthcare support staff involved in their care. The thesis includes four qualitative studies: individual interviews (Studies I and II), lifeworld interviews (Study III), and focus group discussions (Study IV). Different analytical approaches were applied: interpretive description (Thorne, 2004, 2016) in Study I, thematic analysis in Study II, phenomenological analysis based on Reflective Lifeworld Research in Study III, and focus group methodology (Krueger & Casey, 2015) in Study IV. The findings reveal that existential loneliness was particularly prominent early in the migration process, often linked to the loss of a familiar lifeworld (II and III). Additional triggers included thoughts about death and dying in a foreign country, as well as feelings of existential guilt (II). The results also highlight a deep need for meaning, belonging, and opportunities to maintain or rediscover spiritual practices (I–III). Healthcare support staff perceived existential loneliness among older migrants as a sense of alienation and longing for home (IV). Despite their motivation to provide compassionate care, they reported challenges in addressing these experiences, citing time constraints and limited cultural knowledge as significant barriers. An awareness of and a sensitivity to what lies between the lines in interpersonal encounters, ranging from fears to hopes, are of importance when encountering older migrants experiencing existential loneliness. Existential loneliness can lead to significant suffering. For older migrants, having the opportunity to share their life stories and reflect on their experiences can be particularly beneficial, as it helps create meaning and context in their current situation.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.012 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.041 | 0.016 |
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".