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Record W4387303247 · doi:10.24043/001c.88131

The Fourth Estate? The Experiences of Cape Verdean Journalists

2023· article· en· W4387303247 on OpenAlexvenueno aff
Abrak Saati

Bibliographic record

VenueIsland Studies Journal · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicIsland Studies and Pacific Affairs
Canadian institutionsnot available
FundersVetenskapsrådet
KeywordsJournalismFourth EstateInstitutionDemocracyPoliticsState (computer science)CensorshipEstatePolitical scienceSociologyFreedom of the pressJurisdictionCape verdeLawMedia studiesPublic relationsEthnology

Abstract

fetched live from OpenAlex

This article explores how being a small island jurisdiction affects actors in the journalism sector. The media is often referred to as the fourth estate, an institution inherently important for democracy. By scrutinizing politicians, journalists have the possibility to reveal transgressions and provide the public insight into how powerholders are performing as state officials. With this knowledge, the public can make informed decisions as to who will earn their vote in coming elections. This article studies the space for manoeuvre of investigative journalism in a small island state where the interconnectedness of people – journalists, sources, and powerholders – is a fact. It does so by studying the case of Cape Verde, a small island nation with 560 000 residents. Interviews with 12 Cape Verdian journalists from a range of the most important media outlets in the country, reveal that although freedom of expression and freedom of the press are constitutionally guaranteed, there are substantial practical limitations of free journalism. Respondents tell of widespread self-censorship, underfunding, and political interference as aspects that limit the possibility of conducting their work in a manner that would make them the watchdog institution that most of them aspire to and wish they could be.

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 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.143
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0070.001
Scholarly communication0.0000.000
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 head0.046
GPT teacher head0.350
Teacher spread0.304 · 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 teacher head, not a consensus.

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

Citations4
Published2023
Admission routes1
Has abstractyes

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