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Record W3004853325 · doi:10.4000/eccs.2185

La Grande émigration transatlantique, 1870-1914 : le point sur les recherches

2019· article· fr· W3004853325 on OpenAlexaff
Bruno Ramírez

Bibliographic record

VenueÉtudes canadiennes / Canadian Studies · 2019
Typearticle
Languagefr
FieldArts and Humanities
TopicFrench Historical and Cultural Studies
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHumanitiesPolitical scienceEthnologyArtSociology

Abstract

fetched live from OpenAlex

La Grande émigration transatlantique (1870-1914) se caractérise par le volume sans précédents des populations touchées. Toutefois, sa caractéristique principale tient en grande partie à l'apport considérable des régions de l'Europe centrale, orientale, et du sud. Cet article discute comment, surtout à partir des années 1960-1970, cet ensemble de mouvements migratoires est devenu le champ d'étude privilégié permettant à l'histoire des migrations internationales de s'affirmer en tant que composante majeure de la « nouvelle histoire sociale ». Les recherches ont mené à une vaste production historiographique portant sur presque tous les pays ayant participé à ce mouvement transatlantique. Après avoir fait état des méthodologies et des cadres conceptuels que les historiens ont le plus fréquemment adoptés, l'article discute des orientations plus récentes marquées par la multidisciplinarité et influencées par la reconfiguration radicale que les migrations internationales ont connue pendant la deuxième moitié du XXe siècle. Des perspectives axées sur l'analyse du genre (gender analysis), des phénomènes transnationaux, ainsi que sur le rôle de l'état-nation dans la gestion des migrations, ont permis aux historiens de revisiter la grande émigration transatlantique et d'approfondir certains de ses aspects.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.950
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.006
Science and technology studies0.0040.004
Scholarly communication0.0020.002
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.074
GPT teacher head0.229
Teacher spread0.155 · 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 designNot applicable
Domainnot available
GenreReview

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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