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Record W3112821889 · doi:10.29173/cjnser.2020v11n2a379

Les innovations sociales en Afrique subsaharienne

2020· article· fr· W3112821889 on OpenAlexaffvenue
Mebometa Ndongo, Juan‐Luis Klein

Bibliographic record

VenueCanadian journal of nonprofit and social economy research · 2020
Typearticle
Languagefr
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsUniversité du Québec à MontréalUniversity of Ottawa
Fundersnot available
KeywordsHumanitiesPolitical scienceSociologyPhilosophy

Abstract

fetched live from OpenAlex

Cet article dresse l’état des savoirs sur les innovations sociales en Afrique subsaharienne. L’objectif est d’explorer et de mettre en lumière les trajectoires émergentes sur ce sujet encore peu abordé, pour un continent confronté entre l’extraversion des modes de développement dans un contexte de crises multiformes et la dynamique des réalités historiques. Pour cela, l’article revisite les écrits et explore les cas emblématiques en recentrant la recherche sur une temporalité des années 1960 à ce jour où la confrontation des deux mouvements a engendré une hybridation qui articule les innovations. La principale trouvaille concerne, d’une part, la focalisation des innovations sociales sur l’humain portées par des organisations liées à l’économie sociale et, d’autre part, l’arrimage entre les enjeux, les défis et les pratiques dont les repères locaux particularisent ces innovations. Il ressort des cas analysés un ensemble de logiques opératoires marquées par l’interaction des technologies importées et des mécanismes préexistants sur lesquelles les technologies novatrices prennent naissance. Le foisonnement de telles technologies permet d’ouvrir des perspectives de recherche mettant en scène les structures socio--territoriales, l’omniprésence d’activités solidaires et la prédominance des acteurs communautaires devant combiner les dimensions sociale, institutionnelle, économique, technique et académique.

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)0.003
metaresearch head score (Gemma)0.005
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 score0.039
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0060.006
Scholarly communication0.0050.003
Open science0.0010.003
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.286
GPT teacher head0.403
Teacher spread0.117 · 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

Citations3
Published2020
Admission routes2
Has abstractyes

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Same venueCanadian journal of nonprofit and social economy researchSame topicSocial Sciences and GovernanceFrench-language works237,207