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Record W4210283866 · doi:10.3917/sdd.014.0014

Panser les blessures en soignant la mémoire : stratégies de mise en espace des lieux de mémoire d’atrocités

2022· article· fr· W4210283866 on OpenAlex
Anne-Marie Broudehoux, Guylaine Cheli

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSciences du Design · 2022
Typearticle
Languagefr
FieldArts and Humanities
TopicCultural Identity and Heritage
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Cet article étudie le rôle de l’architecture dans l’inscription de la mémoire collective des atrocités de masse dans le paysage urbain. À travers l’analyse d’espaces publics mémoriels situés dans quatre villes européennes, il explore les façons dont l’architecture peut agir comme un langage non verbal apte à traduire, sous une forme matérielle, une réalité trop dure pour être communiquée autrement. Nous soutenons que les qualités esthétiques du mémorial, la relation au site, l’organisation spatiale, le chemin de circulation ainsi que l’utilisation spécifique des matériaux, des textures et des symboles créent un environnement propice à la réceptivité, à l’empathie et à l’introspection. L’article suggère que l’architecture mémorielle peut avoir un effet positif sur les sociétés urbaines, dans le cadre d’un mouvement vers la guérison collective, la réparation historique et la diminution des inégalités sociales.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.667
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0070.003
Scholarly communication0.0020.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.052
GPT teacher head0.263
Teacher spread0.211 · 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