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Record W2025925800 · doi:10.4000/assr.21870

La tombe de Victor Noir au cimetière du Père-Lachaise

2010· article· fr· W2025925800 on OpenAlexaff
Marina Emelyanova-Griva

Bibliographic record

VenueArchives de sciences sociales des religions · 2010
Typearticle
Languagefr
FieldSocial Sciences
TopicDeath, Funerary Practices, and Mourning
Canadian institutionsLibrary and Archives Canada
Fundersnot available
KeywordsArtHumanitiesEthnologyHistory

Abstract

fetched live from OpenAlex

La tombe du journaliste Yvan Salmon, dit Victor Noir (1848-1870), est aujourd’hui l’un des monuments les plus visités du cimetière parisien du Père-Lachaise; elle fait même l’objet d’un véritable culte. La légende veut qu’en frottant le gisant, surtout à l’endroit du sexe, on recouvre fécondité ou virilité. L’étude s’attache à montrer quelles transformations fonctionnelles a connu le gisant de Victor Noir depuis son inauguration jusqu’à nos jours. Le culte originel est politique: journaliste d’opposition, Victor Noir est tué le 10 janvier 1870 lors d’une altercation avec le prince Pierre Bonaparte, cousin de Napoléon III; ses obsèques réunissent plus de cent mille personnes; il devient le symbole de la répression de l’Empire face à la lutte pour la liberté. Le sculpteur républicain Jules Dalou édifie à sa mémoire, en 1891, un gisant de bronze. Dans le courant du xxe siècle, sa tombe acquiert progressivement des connotations et des vertus érotiques: un culte sexuel se substitue définitivement au culte politique à partir des années soixante.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.030
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.003
Scholarly communication0.0040.001
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0170.002

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 head0.050
GPT teacher head0.340
Teacher spread0.289 · 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
Published2010
Admission routes1
Has abstractyes

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