MétaCan
Menu
Back to cohort

Negotiating Legitimacy: Binational Couples in the Face of Immigration Bureaucracy in Belgium and Italy

2021· article· en· W3161294618 on OpenAlexvenueno aff
Laura Odasso

Bibliographic record

VenueAnthropologica · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsnot available
FundersFP7 People: Marie-Curie ActionsCentre National de la Recherche ScientifiqueAgence Nationale de la Recherche
KeywordsLegitimacyBureaucracyAgency (philosophy)ScrutinyImmigrationNegotiationContext (archaeology)GovernmentalitySociologyPolitical sciencePolitical economyPoliticsLawGeographySocial science

Abstract

fetched live from OpenAlex

Drawing from ethnographic research conducted with binational heterosexual couples negotiating their legitimacy in the face of immigration bureaucracy in Belgium and Italy, I explore the interplay between marriage migration governmentality and personal subjectivities. In a context of increased political scrutiny, I illustrate how binational couples wield their intimacy to become and stay legal; and how their experiences of the bureaucratic encounters impact on both partners’ agency, producing swinging emotions and improving their legal culture. In Belgium and Italy, marriage to a citizen remains a pathway towards securing residence for the migrant partner. Hence, in both countries these formalities, that I frame as a network of bordering practices, are increasingly – but differently – policed defining divergent marriage migration regimes but similar shared migratory careers for the couples. The potency of the legal-bureaucratic culture fashions the couples’ journey through immigration law and its street-level implementation. Nevertheless, beyond the opportunity structures and nationally anchored constraints, the analysis demonstrates that the partners’ agency similarly emerges from the migration management at large, their personal legal status and biographical resources, and interactions with intermediaries at the margin of immigration bureaucracy. Such agency – triggered by intimate intentions and expectations – is contingent and relational.

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0110.009
Scholarly communication0.0060.002
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.023
GPT teacher head0.344
Teacher spread0.321 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations18
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueAnthropologicaSame topicMigration and Labor DynamicsFrench-language works237,207