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Record W2922133022 · doi:10.1177/0020715219832918

Relational ambivalence: Exploring the social and discursive dimensions of ambivalence—The case of Turkish aging labor migrants

2019· article· en· W2922133022 on OpenAlexvenueno aff
Monika Palmberger

Bibliographic record

VenueInternational Journal of Comparative Sociology · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsnot available
FundersUniversität WienAustrian Science FundMax-Planck-Institut zur Erforschung Multireligiöser und Multiethnischer Gesellschaften
KeywordsAmbivalenceContext (archaeology)TurkishFeelingNarrativeSociologySocial psychologyGender studiesPsychology

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.391
Threshold uncertainty score0.465

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.081
GPT teacher head0.388
Teacher spread0.306 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations33
Published2019
Admission routes1
Has abstractyes

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