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Record W2028952566 · doi:10.7202/021114ar

L’évolution du nombre des habitants du Nord canadien de 1966 à 1971

2005· article· fr· W2028952566 on OpenAlexvenueaboutno aff
Gilles Cayouette, Louis‐Edmond Hamelin

Bibliographic record

VenueCahiers de géographie du Québec · 2005
Typearticle
Languagefr
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

À partir d'une régionalisation du Nord et à l'aide des documents du Recensement du Canada de 1971, les auteurs ont mis à jour leurs estimations de 1966 de la population du Canada par zone nordique et décrit le comportement démographique entre les deux derniers recensements. Ils ne font que présenter une masse statistique en fonction d'une conception du Nord. 253 559 personnes habitaient le Nord en 1971 soit 1,2% de la population totale du Canada. La nordicité explique la répartition de la population entre le Moyen Nord, le Grand Nord et l'Extrême Nord. De 1966 à 1971, la population du Nord s'est accrue à un rythme un peu plus rapide que celle du Canada de base tout en se densifiant légèrement. Selon la province ou le territoire retenu, l'on assiste à une nordification ou à une denordification assez accentuée. Les disparités de population sont aussi fortes en considérant un découpage vertical du Nord. Les développements miniers, administratifs, hydroélectriques et pétroliers demeurent les facteurs les plus importants de cette évolution.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.016
Threshold uncertainty score0.115

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
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 head0.008
GPT teacher head0.198
Teacher spread0.190 · 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

Citations0
Published2005
Admission routes2
Has abstractyes

Explore more

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