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Record W2342022309 · doi:10.1177/1464884915597159

Triggering change – How investigative journalists in Sub-Saharan Africa contribute to solving problems in society

2015· article· en· W2342022309 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

VenueJournalism · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicMedia Studies and Communication
Canadian institutionsUniversité de MonctonUniversity of OttawaUniversité Laval
FundersMinisterie van Buitenlandse ZakenDepartment for International Development
KeywordsJournalismAction (physics)Government (linguistics)PublishingElement (criminal law)Public relationsPolitical scienceState (computer science)SociologySocial scienceMedia studiesLawComputer science

Abstract

fetched live from OpenAlex

This article analyses 12 cases of investigative journalism in Sub-Saharan Africa. The reporters all claimed to have contributed to change processes by influencing government policy, action by state administration, supporting the uptake of scientific solutions or provoking public debate. An assessment of these processes shows that in 10 cases, the journalists indeed helped to trigger change and in two cases they failed to do so. The cases are evaluated through an explorative approach inspired by the dynamic models for communication on public issues developed by Rucht and Peters. Different types of investigative stories in Sub-Saharan Africa are identified and hypotheses are developed on key factors that were important in investigating and publishing the stories as well as in achieving change. A decisive element of investigative journalism in Sub-Saharan Africa seems to be the involvement of and the interaction with other societal non-journalist actors.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.863
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.170
GPT teacher head0.330
Teacher spread0.159 · 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