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Record W3015568984 · doi:10.55765/atps.i16.447

La radio communautaire et le défi de l’accès à l’information publique en période de crises en Afrique : l’exemple de la République démocratique du Congo

2019· article· fr· W3015568984 on OpenAlexaff
Valentin Migabo

Bibliographic record

VenueRevue internationale animation territoires et pratiques socioculturelles · 2019
Typearticle
Languagefr
FieldAgricultural and Biological Sciences
TopicAgriculture and Rural Development Research
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsPolitical scienceDemocracyPoliticsState (computer science)Consolidation (business)Power (physics)Promotion (chess)HumanitiesLawBusiness

Abstract

fetched live from OpenAlex

Longtemps utilisée comme outil de propagande politique au service du pouvoir, la radio s’est émancipée ces dix dernières années en République démocratique du Congo (RDC). Face à la précarité des infrastructures sociales et à l’absence de l’autorité étatique, les radios communautaires émergent en marge des radios d’État ou commerciales. Administrées par la société civile, elles jouent un rôle prépondérant dans la défense des droits et libertés publiques. Elles participent à la promotion des valeurs démocratiques et à la consolidation de la paix. Leurs émissions dérangent le pouvoir mais rencontrent l’assentiment du peuple parce qu’elles dénoncent les abus, donnent la vraie information et accordent des espaces aux membres de la communauté pour discuter de questions d’intérêts communs. Cependant, les conditions dans lesquelles elles fonctionnent sont déplorables. La plupart n’ont pas d’équipements minimum appropriés et opèrent dans la clandestinité. Les journalistes sont fréquemment arrêtés, voire tués, et leurs maisons fermées. Le texte qui suit fait état de cette vulnérabilité.

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)0.002
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.108
Threshold uncertainty score0.215

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0050.006
Scholarly communication0.0070.003
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0100.001

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 head0.008
GPT teacher head0.264
Teacher spread0.256 · 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
Published2019
Admission routes1
Has abstractyes

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