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Record W2013897571 · doi:10.5539/res.v5n5p111

Information Technology and Journalism Practice in Nigeria: A Survey of Journalists in Portharcourt Metropolis

2013· article· en· W2013897571 on OpenAlexvenueno aff
Godwin B. Okon, Timothy Eleba

Bibliographic record

VenueReview of European Studies · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicMedia Studies and Communication
Canadian institutionsnot available
Fundersnot available
KeywordsJournalismRetrainingSoftware deploymentWork (physics)Information technologyPublic relationsBusinessInformation and Communications TechnologySociologyPolitical scienceComputer scienceEngineeringAdvertisingLaw

Abstract

fetched live from OpenAlex

The thrust of this study was predicated on the need to ascertain the extent to which Nigerian journalists, especially those in Portharcourt metropolis, have integrated the use of information technology (IT) in their professional repertoire. The objectives among others included the need to streamline the challenges, if any, journalists face in the adoption of new information technologies (ITs). The study by its nature necessitated survey. To this end, one hundred and twenty (120) journalists were sampled with a view to dovetailing their responses within a scholarly spectrum. Findings revealed that 67% of the respondents use IT facilities in their day to day operations. Data further revealed that IT facilities in the various media houses studied were obsolete and inadequate. The challenges faced by journalists in the deployment of IT facilities were identified as lack of access to emerging information technologies as well as the absence of a framework for the training and retraining of journalists on information technology hardware and software configurations. It was therefore recommended that media proprietors should provide as part of the work environment, IT facilities to enable journalists discharge their duties in line with international best practices.

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)0.006
metaresearch head score (Gemma)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.448
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.013
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 head0.049
GPT teacher head0.380
Teacher spread0.331 · 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 designObservational
Domainnot available
GenreReview

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
Published2013
Admission routes1
Has abstractyes

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