MétaCan
Menu
Back to cohort
Record W4318071435 · doi:10.5206/mf.v8i1.15875

(Re)penser les frontières des identités dans les littératures, musiques et cinémas francophones

2023· article· fr· W4318071435 on OpenAlexvenueno aff
Richmond Konan, Tite Lattro, Sinan Anzoumana

Bibliographic record

VenueMouvances Francophones · 2023
Typearticle
Languagefr
FieldSocial Sciences
TopicAfrican history and culture studies
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Résumé: Cet ouvrage se propose de questionner l’espace littéraire francophone sur les mutations identitaires complexes et multiples en cours. Mais surtout, analyser la possibilité de construction d’un monde qui refuse de symboliser uniquement l’« autre », au profit de « l’entre-deux » ou du « Tout-monde ». En se fondant sur la pensée de Franz Fanon, Edouard Glissant, Achille Mbembé, d’Olympe de Gouges et ses épigones féministes etc., cet ouvrage interrogera les nouvelles dynamiques identitaires et mettra en débat les frontières au cœur de la cartographie des identités. Le présent ouvrage est composée de 12 contributions interdisciplinaires, classées en 4 axes thématiques. La section initiale qui se focalise sur le trauma colonial et les voies d’une reconstruction identitaire du sujet postcolonial africain s’ouvre avec l’article de Konan Richmond Alain qui analyse Frère d’âme de David Diop, sous l’angle d’une conscience mémorielle afrocentrée. La deuxième partie concentre des textes qui mettent en relief la confrontation des identités en contexte (trans) migratoire. La troisième section s’intéresse aux manifestations identitaires dans les arts, musiques et cinéma. L’ultime articulation s’intéresse aux mythes qui traduisent les imaginaires et les identités des peuples.

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: none
Teacher disagreement score0.221
Threshold uncertainty score0.440

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.008
Scholarly communication0.0060.003
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0150.001

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 head0.033
GPT teacher head0.292
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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueMouvances FrancophonesSame topicAfrican history and culture studiesFrench-language works237,207