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Record W2423943698 · doi:10.1080/02500167.2016.1167753

Media–state relations in Burundi: Overview of a post-traumatic media ecology

2016· article· en· W2423943698 on OpenAlexaff
Oumar Kane, Aimé-Jules Bizimana

Bibliographic record

VenueCommunicatio · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicAfrican history and culture studies
Canadian institutionsUniversité du Québec en OutaouaisUniversité du Québec à Montréal
Fundersnot available
KeywordsMedia ecologyState (computer science)EcologyPolitical ecologyPolitical scienceGeographySociologyMedia studiesBiologyComputer scienceLawPolitics

Abstract

fetched live from OpenAlex

Through an analysis of the relations between the state and the media in Burundi, this article aims to problematise these actors’ interactions within a context characterised by an asymmetry of power in favour of political authorities and some leeway enjoyed by the media. Through a review of a corpus constituted of scientific literature, reports documenting the situation of press freedom in the country, and newspaper articles, the present article shows that the legal framework governing media activity is rather protective of press freedom, despite some recent setbacks. Under this protective media context, the state uses a variety of devious means to strengthen its grip on the media sector and on journalists. The media, for their part, are obliged to manoeuvre in a post-traumatic context where issues of security have a strong public legitimacy. The article shows that in order to understand relations between the Burundian state and the media, it is necessary to place them in an asymmetrical power context where both face constraints and enjoy spaces of tactical intervention.

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)0.003
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: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0070.010
Science and technology studies0.0100.014
Scholarly communication0.0100.007
Open science0.0010.008
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.084
GPT teacher head0.338
Teacher spread0.254 · 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

Citations5
Published2016
Admission routes1
Has abstractyes

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