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Record W4410591330 · doi:10.4000/1401n

Reposer auprès de ses proches : la sépulture à Montpellier à la fin du Moyen Âge

2024· article· fr· W4410591330 on OpenAlexaff
Lucie Laumonier

Bibliographic record

VenueMédiévales · 2024
Typearticle
Languagefr
FieldSocial Sciences
TopicMedieval and Early Modern Justice
Canadian institutionsConcordia University
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Cet article est un préliminaire à une analyse détaillée des élections de sépulture auprès de proches (sépulture « familiale ») à Montpellier et dans le diocèse de Maguelone à la fin du Moyen Âge. Il vise à en poser les fondements géographiques, méthodologiques et statistiques. La question de la géographie de l’ensevelissement, largement défrichée par des études plus anciennes, demeure périphérique au propos – elle sera uniquement abordée afin de compléter les travaux préexistants pour la fin du xive et du xve siècle. Le cœur de la recherche est celui des demandes d’ensevelissement auprès de proches, dans une perspective chronologique et méthodologique. En moyenne, 60 % des testateurs et testatrices de Montpellier demandaient à être ensevelis auprès de membres de leur parenté (c. 1250-1500). On verra que les demandes de sépulture familiale étaient devenues dès le début du xve siècle une clause quasi-incontournable des testaments de la ville – présents dans trois quarts des actes à la fin de la période – et que l’étude typologique de ces requêtes témoigne d’enjeux individuels et d’une perception personnelle, fluide et mouvante de la parenté.

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)0.002
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 score0.050
Threshold uncertainty score0.099

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0120.001

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 head0.028
GPT teacher head0.287
Teacher spread0.259 · 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
Published2024
Admission routes1
Has abstractyes

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