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Record W4388968959 · doi:10.3828/qs.2023.17

<i>“This was a little world at which I was looking”</i> : Le Québec des années 1930 vu par le <i>National Geographic Magazine</i>

2023· article· fr· W4388968959 on OpenAlexaffabout
Pierre-Olivier Bouchard

Bibliographic record

VenueQuebec Studies · 2023
Typearticle
Languagefr
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Ce texte s’intéresse à la représentation du Québec dans les quatre articles illustrés du National Geographic Magazine publiés dans les années 1930. L’analyse montre comment les éléments propres à la poétique du magazine sont modulés en fonction de la réalité du Québec de l’époque. Il y apparait que la vision du monde véhiculée par le magazine se manifeste notamment par le choix des lieux visités par les reporters, les photographies illustrant les articles, et surtout par un discours sur la place de la modernité et de l’histoire dans la société québécoise. Dans les pages du magazine, cette dernière apparait comme figée dans son histoire et dans ses traditions, ce qui ferait d’elle non pas une société « sans histoire » (au sens anthropologique, comme beaucoup de sociétés représentées dans le magazine à la même époque), mais plutôt une société réfractaire à la modernité et obnubilée par le culte des ancêtres. Entre les lignes se profilent également les préoccupations des auteurs américains à une époque où leur pays est affligé par la sécheresse et par une crise économique.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.057
Threshold uncertainty score0.237

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0120.007
Scholarly communication0.0070.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0220.002

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 head0.030
GPT teacher head0.260
Teacher spread0.230 · 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 designNot applicable
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
Published2023
Admission routes2
Has abstractyes

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