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Record W4281717685 · doi:10.1080/01436597.2022.2077185

What role do social accountability actors play in resisting media capture in sub-Saharan Africa? Evidence from Ghana

2022· article· en· W4281717685 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThird World Quarterly · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicMedia Influence and Politics
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsAccountabilityJournalismSocial mediaPublic relationsPolitical scienceEmpowermentSociologyDenunciationPower (physics)LawPolitics

Abstract

fetched live from OpenAlex

Although media capture is a global issue, it is a particularly significant problem in sub-Saharan African countries like Ghana. Media capture occurs when media organisations become incapable of performing critical watchdog functions, such as fighting corruption and human rights violations, because of pressures from capital and power. This article addresses a fundamental question: In Ghana’s Fourth Republic, what role do social accountability actors play in resisting media capture by capital and power? I argue that social accountability actors perform three essential, interrelated roles: (1) defending media freedoms and independence, (2) activating and facilitating the media’s work and (3) legitimising and encouraging critical journalism. In doing so, they use a combination of strategies – from advocacy, denunciation and legal action to establishing and funding non-profit media outlets to do investigative journalism. This work extends the literature by examining the crucial role social accountability actors play in counteracting media capture so that critical journalism can do its job.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.297
Threshold uncertainty score0.965

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.042
GPT teacher head0.312
Teacher spread0.270 · 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