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Record W7131413876 · doi:10.7202/1123555ar

Concurrences mémorielles en milieu minoritaire : le paradoxe hearstois

2025· article· fr· W7131413876 on OpenAlexaffvenueabout
Marie LeBel, Melissa Vernier

Bibliographic record

VenueMens Revue d histoire intellectuelle et culturelle · 2025
Typearticle
Languagefr
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsUniversité de Hearst
Fundersnot available
KeywordsVisionContext (archaeology)Face (sociological concept)Confessional

Abstract

fetched live from OpenAlex

Cet article présente les réflexions historiographiques des autrices en lien avec les concurrences mémorielles rencontrées dans la réalisation de projets commémoratifs pour le centenaire de Hearst, dans le nord de l’Ontario. La publication d’un ouvrage d’histoire, l’écriture et la scénographie d’archives à voix haute ainsi que la conception d’un jeu d’évasion ont révélé des visions et des sensibilités mémorielles différentes, sinon divergentes, entre la majorité francophone et la minorité anglophone de la communauté. L’article utilise, entre autres, les concepts de champ d’expérience, d’horizon d’attente et de régime d’historicité pour illustrer, à partir de ces projets, les ajustements interprétatifs requis face à la plurivocité mémorielle en contexte de commémoration.

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)0.008
metaresearch head score (Gemma)0.021
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.406
Threshold uncertainty score0.816

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0250.053
Scholarly communication0.0130.007
Open science0.0020.012
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0070.000

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 head0.011
GPT teacher head0.246
Teacher spread0.235 · 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
Published2025
Admission routes3
Has abstractyes

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