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Record W1644691029 · doi:10.4000/lisa.8789

Sur les traces de John MacCrae, ou l’inscription dans l’espace public du souvenir d’un combattant de 1914-1918

2022· article· fr· W1644691029 on OpenAlexaboutno aff
Emmanuelle Danchin

Bibliographic record

VenueRevue LISA / LISA e-journal · 2022
Typearticle
Languagefr
FieldArts and Humanities
TopicHistorical Studies and Socio-cultural Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

John MacCrae (1872-1918), engagé volontaire dans le corps d’armée canadien dès 1914, est à l’origine du choix du symbole du coquelicot adopté dès 1921 par les pays du Commonwealth en souvenir des combattants tombés sur le champ de bataille. En partant de l’exemple de Wimereux dans le Pas-de-Calais, où il est enterré, il s’agira de voir ce qui perdure du souvenir de cet homme. Peut-on considérer Wimereux comme un lieu de mémoire ou de commémoration ? Quelles traces subsistent aujourd’hui de son passage ? Depuis quand et où est-il honoré ? Qui honore-t-on exactement ? En quoi ce lieu diffère-t-il des autres lieux qui lui sont consacrés ? L’exemple de MacCrae sera aussi l’occasion de réfléchir à la constitution de traces matérielles et immatérielles (internet), ainsi qu’à la circulation d’icônes, qui construisent dans le temps des traces mémorielles dans l’espace public. Ce qui importe, en effet, n’est pas tant le personnage que ses traces et ce qu’elles nous disent aujourd’hui d’un conflit maintenant centenaire.

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)0.004
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: none
Teacher disagreement score0.915
Threshold uncertainty score0.170

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.009
Scholarly communication0.0050.004
Open science0.0000.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0200.002

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 head0.029
GPT teacher head0.207
Teacher spread0.179 · 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
Published2022
Admission routes1
Has abstractyes

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