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Record W4386994589 · doi:10.3917/etsoc.176.0169

Dieu, le sang, YouTube et la rue

2023· article· fr· W4386994589 on OpenAlexaff
Aurélie Doignon

Bibliographic record

VenueLes Études Sociales · 2023
Typearticle
Languagefr
FieldSocial Sciences
TopicAfrican Studies and Ethnography
Canadian institutionsEspace pour la vie
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Évoquant un « don de Dieu », ou le fait d’avoir la danse « dans le sang », les danseurs de sabar , au Sénégal, prétendent avoir fait carrière sans passer par des apprentissages, tout en revendiquant plus tard d’avoir eu accès à certaines formations ou stages. En Afrique de l’Ouest, les usages du champ lexical de la vocation, très opérant dans le milieu artistique, se distinguent des usages français (en particulier à travers les apprentissages lignagers). En effet, les figures d’apprentissage et de transmission ne peuvent être comparées aux pratiques occidentales que nous connaissons. Les formes et les sentiments d’autodidaxie qui sont à l’œuvre sont mis en parallèle avec les structures informelles d’apprentissage.

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)0.000
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.075
Threshold uncertainty score0.150

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0040.002
Scholarly communication0.0050.004
Open science0.0000.002
Research integrity0.0010.001
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 head0.134
GPT teacher head0.375
Teacher spread0.241 · 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 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

Citations1
Published2023
Admission routes1
Has abstractyes

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