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Record W2169338405 · doi:10.7202/039989ar

Une analyse provinciale de la migration de remplacement au Canada

2010· article· fr· W2169338405 on OpenAlexaffvenueabout
Alain Bélanger

Bibliographic record

VenueCahiers québécois de démographie · 2010
Typearticle
Languagefr
FieldHealth Professions
TopicGlobal Health Care Issues
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsPolitical scienceImmigrationHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

L’étude des Nations unies (2000) intitulée « Replacement migrations : Is it a solution to declining and aging population ? » montre que l’immigration à elle seule ne saurait être une solution viable au vieillissement démographique. La situation démographique canadienne diffère de celles des pays analysés dans le rapport des Nations unies, notamment par son taux d’immigration parmi les plus élevés au monde. Contrairement aux idées reçues, les taux actuels d’immigration sont amplement suffisants pour assurer le maintien de la population canadienne et même de sa population en âge de travailler à des niveaux supérieurs à ceux observés actuellement à court, moyen et même long terme. Par contre, compte tenu de la concentration spatiale des immigrants à leur arrivée, une analyse des conséquences démographiques de l’immigration de remplacement au niveau provincial montre qu’une répartition plus égale des immigrants sur le territoire pourrait s’avérer plus efficace qu’une simple hausse des niveaux d’immigration.

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)0.001
metaresearch head score (Gemma)0.005
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 score0.062
Threshold uncertainty score0.447

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0040.013
Science and technology studies0.0040.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.008
GPT teacher head0.324
Teacher spread0.316 · 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

Citations2
Published2010
Admission routes3
Has abstractyes

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