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Record W2771076405

Terre de l’ombre ou terre d’abondance? Le Nord des Inuit

2008· article· fr· W2771076405 on OpenAlexaboutno aff
Louis‐Jacques Dorais

Bibliographic record

VenueArchipelago (Université du Québec à Montréal) · 2008
Typearticle
Languagefr
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesEthnologyPolitical scienceGeographyArtHistory
DOInot available

Abstract

fetched live from OpenAlex

Il peut s’avérer intéressant de s’interroger sur l’imaginaire nordique des Inuit. En tant qu’occupants autochtones de ce que nous percevons comme « le Nord », comment conçoivent-ils leur territoire ancestral? Et qu’est-ce que « le Sud » signifie pour eux? Pour trouver les clés donnant accès à cette vision des choses, nous puisons à deux sources : les mots de leur langue – l’inuktitut – définissant le territoire nordique, sa position géographique et les gens qui l’habitent, et la perception de ce territoire exprimée dans les textes d’auteurs inuit du Nunavik (nord du Québec) et de la région de Baffin au Nunavut. Tant les mots de l’inuktitut que les quelques textes étudiés semblent montrer trois choses : 1) le Nord est le pays des Inuit, inuit nunangat, et en tant que tel, ses occupants s’y sentent tout à fait à l’aise et n’auraient pas idée de le quitter pour aller s’installer ailleurs; 2) c’est un bon pays, plein de ressources de toutes sortes, qui procure une aisance relative et un bonheur certain à ceux qui y vivent; 3) l’inuit nunangat peut cependant se montrer dure, parfois même effrayante, et afin de profiter de ses bienfaits, il faut obligatoirement posséder le savoir nécessaire à l’exploitation judicieuse de ses ressources naturelles et paranaturelles.

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)0.002
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: none
Teacher disagreement score0.428
Threshold uncertainty score0.862

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.010
Scholarly communication0.0060.003
Open science0.0010.001
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 head0.020
GPT teacher head0.236
Teacher spread0.215 · 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

Citations7
Published2008
Admission routes1
Has abstractyes

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