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Record W7001510830

La construction sociale de la migration : Le rôle de l'expérience et des représentations sociales = Social construction of migration: the role of experience and social representations

2017· article· fr· W7001510830 on OpenAlexaboutno aff

Bibliographic record

VenueProject Muse (Johns Hopkins University) · 2017
Typearticle
Languagefr
FieldSocial Sciences
TopicEurasian Exchange Networks
Canadian institutionsnot available
Fundersnot available
KeywordsSocial constructionismSocial representationExploratory analysisExploratory researchIdentity (music)Population
DOInot available

Abstract

fetched live from OpenAlex

L'article présente les résultats d'une enquête exploratoire effectuée en Moldavie sur les représentations sociales des 18 jeunes, 9 migrants et 9 non-migrants, et leurs expériences sociales qui façonnent leur rapport à l'émigration au Canada. L'analyse des éléments représentationnels, suite à une technique d'évocation ainsi que l'analyse de contenu intégrée des entrevues semi-dirigées ont révélé des configurations représentationnelles et expérientielles qui permettent de relativiser les explications de la migration avancées par les théories économiques et du choix rationnel. Abstract: The article presents the results of an exploratory survey among 18 young Moldavans of which 9 reported having taken the decision to permanently settle in Canada and 9 others who have not taken a decision to emigrate from their country. The analysis of representational elements following a technique of evocation, as well as the content analysis of semi-structured interviews, has revealed distinct social representations and social experiences of these two categories of respondents. These results allow us to relativize the explanations of international migration advanced by economic and rational choice theories.

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)0.004
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 score0.080
Threshold uncertainty score0.160

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.022
Scholarly communication0.0070.003
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.033
GPT teacher head0.318
Teacher spread0.285 · 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
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueProject Muse (Johns Hopkins University)→Same topicEurasian Exchange Networks→French-language works237,207→