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Record W3107285334 · doi:10.7202/1072751ar

Les données numériques post mortem et les référents culturels au Cameroun. Un essai d’analyse

2020· article· fr· W3107285334 on OpenAlexvenueno aff
Léopold Maurice Jumbo

Bibliographic record

VenueFrontières · 2020
Typearticle
Languagefr
FieldHealth Professions
TopicAging, Elder Care, and Social Issues
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceSociologyPhilosophy

Abstract

fetched live from OpenAlex

Le fait d’étudier des sujets tabous – en ce sens qu’ils font toujours l’objet de déni et d’effroi − comme le rapport à la mort, la représentation de la survivance de l’âme et les rites funéraires traditionnels ou numériques présente un intérêt à plusieurs points de vue. D’abord, sur le plan phénoménologique, il s’agit d’observer et de décrire les nouvelles pratiques communicationnelles dans l’espace socioculturel. Puis, sur le plan méthodologique, la démarche de recherche sollicite les apports de diverses disciplines qui vont de l’anthropologie à la sociologie de la mort en passant par les sciences de l’information et de la communication. Cet article analyse les « nouvelles liaisons » avec les morts à l’aune du numérique (Bourdeloie et al. , 2016) à partir de données recueillies au Cameroun. En favorisant l’émancipation des cultures face à certaines contraintes, Internet oblige à repenser les modes de médiation avec l’au-delà. Les résultats de cette recherche montrent que même dans un contexte de faible pénétration d’Internet et de fortes croyances dans l’efficacité des rites traditionnels cette technologie bouleverse les usages et se révèle un dispositif d’accompagnement plutôt que de substitution.

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 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.227
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.054
GPT teacher head0.356
Teacher spread0.302 · 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; both teacher heads agree on what is shown here.

Study designQualitative
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
Published2020
Admission routes1
Has abstractyes

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