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Record W2141593698 · doi:10.7202/1003588ar

Les sources administratives à l’aide de la statistique sociale : l’apport du Registre des Italiens résidant à l’étranger pour l’analyse régionale de la migration de retour

2011· article· fr· W2141593698 on OpenAlexvenueaboutno aff
Daniela Ghio

Bibliographic record

VenueCahiers québécois de démographie · 2011
Typearticle
Languagefr
FieldSocial Sciences
TopicUrban, Neighborhood, and Segregation Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesArt

Abstract

fetched live from OpenAlex

Nous proposons une approche comparative origine-destination pour expliquer la dynamique du retour à partir de l’analyse de la relation entre la migration de retour et le maintien de la citoyenneté du pays d’origine. En nous appuyant sur une source de données rendue exceptionnellement accessible, le Registre des Italiens résidant à l’étranger, nous formulons l’hypothèse suivante : le comportement du retour de la population italienne immigrée au Canada est relié au maintien de la citoyenneté italienne. Pour tester cette hypothèse, nous reconstruisons le cadre historique de la migration italienne au Canada depuis 1966, selon les phases du calendrier censitaire, en focalisant la période la plus récente 2001-2006. L’adoption de la méthodologie multirégionale (Rogers, 1995) permet de retracer les trajectoires migratoires de la population italienne immigrée au Canada en recréant le système d’interaction entre les phénomènes démographiques et les changements du statut juridique, de la citoyenneté italienne d’origine à la naturalisation canadienne. La recherche atteste l’existence d’une corrélation positive entre le comportement migratoire de retour des immigrants italiens au Canada et la conservation du statut de citoyens italiens.

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)0.010
metaresearch head score (Gemma)0.042
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 score0.331
Threshold uncertainty score0.658

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.042
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0170.031
Science and technology studies0.0030.002
Scholarly communication0.0090.003
Open science0.0020.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.002

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 head0.042
GPT teacher head0.291
Teacher spread0.249 · 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
Published2011
Admission routes2
Has abstractyes

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