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Record W4387894630 · doi:10.31124/advance.24407695

Citizen Journalism and Editorial Policies: A Case Study of The Trinidad Express Newspaper

2023· preprint· en· W4387894630 on OpenAlexaff
Prahalad Sooknanan, Kimberly Rojas

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicMaritime Ports and Logistics
Canadian institutionsUniversity of the Fraser Valley
Fundersnot available
KeywordsNewspaperJournalismPublishingDigitizationPolitical sciencePublic relationsContent analysisSociologyMedia studiesSocial scienceEngineeringLaw

Abstract

fetched live from OpenAlex

<p> Abstract The study investigates policies regarding the regulation and control of citizens’ content published by the Trinidad Express Newspaper. A qualitative approach was adopted for the undertaking of this study, which consisted of eight (8) individual semi-structured interviews inclusive of editors and journalists/reporters from the traditional newsroom. The study aimed to answer the following research questions (RQs): RQ1.What are the steps/procedures taken by traditional journalists/reporters in handling of citizen journalism? RQ 2. In what ways have the steps/procedures taken influenced the publishing of citizens’ information? Findings reveal while there are no specific policies geared toward the control of information shared by citizens, the Newspaper has been controlling the flow of information received from the public by implementing the official One Caribbean Media (OCM) Statement of Editorial Principles and Operational Guidelines which inform the work and conduct of those who are part of the production and delivery of news and other content across varying media platforms. More significantly, the study found the free flow of information by citizens negatively impacted the traditional print media. Further, the free flow of information on various media platforms encouraged traditional media (newspapers) to embark on the digitization of newspapers in the Republic of Trinidad and Tobago. </p>

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)0.000
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.264
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.035
GPT teacher head0.270
Teacher spread0.235 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations0
Published2023
Admission routes1
Has abstractyes

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