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Record W4386390400 · doi:10.3917/migra.192.0071

Transnationalisation de l’espace familial et distension des liens familiaux

2023· article· fr· W4386390400 on OpenAlexaboutno aff
Monica Schlobach

Bibliographic record

VenueMigrations Société · 2023
Typearticle
Languagefr
FieldSocial Sciences
TopicMigration, Ethnicity, and Economy
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

La plupart des études sur les familles transnationales soulignent l’existence en leur sein de liens de solidarité et d’entraide, et ce, malgré la distance et la dispersion géographique. Ces travaux mettent en évidence la circulation du Care , les visites et les transferts d’argent, ainsi qu’une coprésence virtuelle rendue possible grâce aux Technologies de l’information et de la communication ( tic ). Dans plusieurs cas, la famille transnationale est présentée comme un modèle d’organisation familiale socialement légitime, en minimisant les effets de la distance sur l’évolution des liens familiaux. Ce texte aborde cette question à partir d’une recherche multi-située réalisée auprès de membres de familles transnationales brésiliennes vivant à Montréal et au Brésil. L’analyse des données a montré que l’éloignement géographique agit comme une barrière dans l’expression de la solidarité familiale transnationale et qu’il a des effets spécifiques sur la dynamique des relations familiales. Trois thèmes sont ici exposés, qui éclairent une face cachée des liens familiaux transnationaux : la difficile redéfinition de certains rôles familiaux ; l’incertitude relative aux conditions de la transmission intergénérationnelle au sein des familles ; et enfin, l’éloignement géographique qui entraîne un sentiment de perte affective.

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)0.003
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.509
Threshold uncertainty score0.987

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0070.009
Scholarly communication0.0050.004
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.000

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 head0.063
GPT teacher head0.349
Teacher spread0.286 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

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