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Record W2587077594 · doi:10.4000/assr.27839

Le sacrifice comme mode de construction

2016· article· fr· W2587077594 on OpenAlexaff
Agnieszka Kedzierska-Manzon

Bibliographic record

VenueArchives de sciences sociales des religions · 2016
Typearticle
Languagefr
FieldSocial Sciences
TopicAfrican Studies and Ethnography
Canadian institutionsNortel (Canada)
Fundersnot available
KeywordsHumanitiesPhilosophyArt

Abstract

fetched live from OpenAlex

En pays mandé (Mali, Côte d’Ivoire, Guinée), l’usage de certains artefacts matériels pour influer sur le destin collectif et individuel est très répandu. De taille et forme variées, ces artefacts fonctionnent comme des sujets dotés d’une capacité d’action dans l’expérience de leurs partenaires humains qui leur adressent la parole et les sacrifices sanglants. Contrairement à l’interprétation classique de tels sacrifices comme mode de communication avec l’invisible, l’analyse des « affordances » du sang mobilisées dans leur cadre révèle qu’ils s’apparentent davantage à un mode de construction. En raison de son caractère polymorphe tant sur le plan de la consistance que celui de la couleur, le sang sacrificiel, versé sur ces dieux toujours en devenir que sont les fétiches, joue un rôle essentiel dans leur constitution et leur conceptualisation, permettant de les façonner de manière sans cesse renouvelée. Offrant aux humains nécessiteux un interlocuteur à jamais inachevé mais à vocation de persister, le sacrifice ouvre ainsi la porte au changement continu et aux négociations permanentes des rapports sociaux existants de même qu’à la création des nouveaux arrangements dans un univers perpétuellement en mutation.

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)0.002
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 score0.013
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.019
Scholarly communication0.0080.005
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0130.001

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 head0.103
GPT teacher head0.349
Teacher spread0.246 · 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

Citations8
Published2016
Admission routes1
Has abstractyes

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