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Record W2788407816 · doi:10.4000/hommesmigrations.4024

Katrina Kalda, Le pays où les arbres n’ont pas d’ombre

2017· article· fr· W2788407816 on OpenAlexaff
Mustapha Harzoune

Bibliographic record

VenueHommes & migrations · 2017
Typearticle
Languagefr
FieldSocial Sciences
TopicAfrican Studies and Ethnography
Canadian institutionsWorld Federation of Science Journalists
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

Citoyen du monde par son statut de musicien et Parisien de cœur, Moh ! Kouyaté partage sa vision d’une nouvelle Afrique de son point de vue de Guinéen. L’art du continent dont se nourrit son œuvre est connecté à toute la planète. Il en a l’expérience par ses tournées américaines, européennes. Alors qu’il s’est d’abord forgé un nom comme guitariste et orchestrateur auprès de nombreux artistes, un premier album remarqué en 2015, Loundo (Un jour), lui permet de donner près de 200 concerts avec son propre groupe. Le titre de son nouvel album Fé Toki (Point de vue), paru au printemps 2017, laisse entendre que tout est question de point de vue… Retraçons avec lui son parcours artistique.

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)0.000
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 score0.014
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0140.002

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 head0.310
Teacher spread0.260 · 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
Published2017
Admission routes1
Has abstractyes

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