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Record W2791779522 · doi:10.1177/0020715218760382

<i>Refugees and citizens</i> : Understanding Eritrean refugees’ ambivalence towards homeland politics

2018· article· en· W2791779522 on OpenAlexvenueno aff
Milena Belloni

Bibliographic record

VenueInternational Journal of Comparative Sociology · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicAfrican history and culture analysis
Canadian institutionsnot available
Fundersnot available
KeywordsAmbivalenceHomelandRefugeePoliticsPolitical scienceState (computer science)DisenchantmentPolitical economySociologyNormativeGender studiesSocial psychologyLawPsychology

Abstract

fetched live from OpenAlex

This article revisits ambivalence as a protracted state which does not simply develop as a result of the migration experience but stems from overlapping levels of normative inconsistency. Drawing from my ethnography of Eritreans’ everyday life in the homeland and abroad, I analyse their attitudes of patriotism and disenchantment through an ambivalence lens. Their ambiguous attitudes are arising from national and transnational Eritrean state policies and are further complicated by their role as “political refugees” in host countries. My informants’ ambivalence stems from them embodying more than one role (i.e. patriots, family breadwinners, refugees from and citizens of their homeland), from contradictory expectations pertaining to the same role (i.e. young citizens in Eritrea) and from clashing implications of being members of two different social systems (i.e. the destination country and the country of origin). Thus, Eritreans’ political loyalties and actions are characterised by a state of ambivalence throughout their migration process. Despite its peculiar characteristics, this case study sheds light on the complexity of ambivalence, as more than a temporary condition, for migrants and refugees in particular. In the current scenario of emigrant states’ transnational governance, protracted ambivalence is likely to mark the attitudes of an increasing number of people on the move as both refugees from and citizens of their country of origin.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.527
Threshold uncertainty score0.860

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 studies0.0000.002
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 head0.059
GPT teacher head0.381
Teacher spread0.322 · 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 designTheoretical or conceptual
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

Citations25
Published2018
Admission routes1
Has abstractyes

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