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Record W7020024423

The intersection of gender and generation in Albanian migration, remittances and transnational care

2009· article· en· W7020024423 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsEmigrationPower (physics)Intersection (aeronautics)Quarter (Canadian coin)PoliticsGender relationsImmigration
DOInot available

Abstract

fetched live from OpenAlex

The Albanian case represents the most dramatic instance of post-communist migration: about one million Albanians, a quarter of the country's total population, are now living abroad, most of them in Greece and Italy, with the UK becoming increasingly popular since the late 1990s. This paper draws on three research projects based on fieldwork in Italy, Greece, the UK and Albania. These projects have involved in-depth interviews with Albanian migrants in several cities, as well as with migrant-sending households in different parts of Albania. In this paper we draw out those findings which shed light on the intersections of gender and generations in three aspects of the migration process: the emigration itself, the sending and receiving of remittances, and the care of family members (mainly the migrants' elderly parents) who remain in Albania. Theoretically, we draw on the notion of `gendered geographies of power and on how spatial change and separation through migration reshapes gender and generational relations. We find that, at all stages of the migration, Albanian migrants are faced with conflicting and confusing models of gender, behavioural and generational norms, as well as unresolved questions about their legal status and the likely economic, social and political developments in Albania, which make their future life plans uncertain. Legal barriers often prevent migrants and their families from enjoying the kinds of transnational family lives they would like.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.425
Threshold uncertainty score0.959

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.288
Teacher spread0.260 · 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

Citations1
Published2009
Admission routes1
Has abstractyes

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