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Record W2940760879

Does Entrance With Family Influence The Way Minors Leave A Refugee Centre

2019· preprint· en· W2940760879 on OpenAlexaboutno aff
Manuela Stranges, François‐Charles Wolff

Bibliographic record

VenueRePEc: Research Papers in Economics · 2019
Typepreprint
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsnot available
Fundersnot available
KeywordsRefugeeQuarter (Canadian coin)Demographic economicsGeographyDemographyIrregular migrationPolitical scienceGenealogySociologyHistoryLawEconomicsEconomic geography
DOInot available

Abstract

fetched live from OpenAlex

This paper investigates the trajectories of young migrants arriving in Italy by sea by means of unique data from a centre for reception of refugees and asylum seekers located in the southern region of Calabria during the period 2009-2014. We focus on the influence of family relationships at entry. We find that the length of stay is nearly five times higher for minors who entered in the centre with family than for those arrived alone. More than one-half of minors choose to leave the centre voluntarily and around a quarter are transferred to other places. A multivariate analysis shows that family status is very influential when explaining time spent in the centre. There is substantial heterogeneity in exit motives depending on the minors’ country of origin. Overall, our results raise the issue of the effectiveness of the whole asylum system in Europe since the massive early departures of minors from the centre may suggest that Italy is not their intended destination.

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)0.001
metaresearch head score (Gemma)0.006
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.022
GPT teacher head0.328
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 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

Citations0
Published2019
Admission routes1
Has abstractyes

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Same venueRePEc: Research Papers in Economics→Same topicMigration, Health and Trauma→French-language works237,207→