Relational ambivalence: Exploring the social and discursive dimensions of ambivalence—The case of Turkish aging labor migrants
Bibliographic record
Abstract
Many of Vienna's labor migrants who entered Austria as so-called "guest workers" together with their spouses long nurtured the dream of returning to their country of origin, at the latest when they retired. By then, however, returning became less than straightforward leading to ambivalence regarding questions of belonging/return and transnational mobility and late-life care. Based on rich qualitative data, in this article, I show that ambivalences are found in the complexity of migrants' narratives, particularly in the way they (1) reassess past choices, (2) negotiate feelings of belonging, and (3) assess future options for late life and care. I argue that the social dimension of ambivalence, which I term "relational ambivalence," is crucial to understanding the labor migrants' experiences, reflections, and choices. The analysis shows that ambivalence must be understood as a product of relationships rather than solely an individual experience. The concept of relational ambivalence captures these social and discursive dimensions of ambivalence. The article ultimately carves out the particularity of ambivalence in the general context of migration and in the specific context of Vienna's labor migrants, while accepting feelings of ambivalence or the simultaneity of different, opposing positions in one and the same person as a core human experience.
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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.019 | 0.028 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.003 |
| 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".