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Record W1523535263

L’attraction d’immigrants entrepreneurs est-il le meilleur moyen de changer le destin économique provincial?

2014· article· fr· W1523535263 on OpenAlex
Leyla Sall, Mathieu Wade

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of New Brunswick Studies / Revue d’études sur le Nouveau-Brunswick · 2014
Typearticle
Languagefr
FieldSocial Sciences
TopicMigration, Ethnicity, and Economy
Canadian institutionsUniversité du Québec à MontréalUniversité de Moncton
Fundersnot available
KeywordsHumanitiesImmigrationResidencePolitical scienceGeographyEthnologyArtSociologyDemography
DOInot available

Abstract

fetched live from OpenAlex

Le Canada accueille en moyenne 250 000 a 260 000 immigrants permanents chaque annee. Toutefois, 80% des immigrants choisissent de vivre dans les provinces de l’Ontario, du Quebec et de la Colombie-Britannique. En fait, ce n’est pas surprenant puisque les trois metropoles du pays: Toronto, Montreal et Vancouver sont dans ces trois provinces et la plupart des immigrants internationaux choisissent les grandes villes comme lieux de residence. La volonte recente des petites provinces des maritimes, a predominance rurales, d’attirer et de retenir une part du flux des immigrants qui s’installent au Canada, fait face a de nombreux defis. Depuis le debut des annees 2000, le Nouveau-Brunswick use de ses droits constitutionnels pour selectionner des immigrants entrepreneurs a qui elle propose le role de dynamiseurs pour rehausser son contexte economique morose. Pour ce faire, une « gouvernementalite » subtile de l’immigration a ete mise en place afin de ne pas heurter les sensibilites des habitants de cette province pauvre.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.611
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0000.003
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.053
GPT teacher head0.280
Teacher spread0.226 · 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