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Record W2548036394

Exploring the Factors Affecting Press Freedom in Nigeria

2016· article· en· W2548036394 on OpenAlexvenueno aff
Oberiri Destiny Apuke

Bibliographic record

VenueHigher education of social science · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicCommunication Studies and Media
Canadian institutionsnot available
Fundersnot available
KeywordsFreedom of the pressConstitutionCensorshipSecrecyFreedom of informationGovernment (linguistics)LawJournalismSociologyStatutory lawPolitical sciencePolitics
DOInot available

Abstract

fetched live from OpenAlex

Press freedom has become one of the major challenges facing Journalism practice in the world. This paper explores the factors hindering press freedom in Nigeria using some relevant examples. The researcher used the qualitative method of research; using secondary data comprising of books and journals. The study is embedded on social responsibility theory. The study reveals that there are a lot of factors in Nigeria that hinders press freedom ranging from secrecy, legal pressure, direct censorship and force among others. Findings also reveal that Nigerian press freedom is a paradox and only exist on paper i.e. in the constitution but not in practice. The study recommends that since press freedom is granted in the constitution of Nigeria, there should be statutory backup and in order not to hinder press freedom, journalist should be allowed to have access to government sources and records so long as it will not bring chaos to the society at large.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0050.005
Scholarly communication0.0060.004
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.147
GPT teacher head0.385
Teacher spread0.238 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations5
Published2016
Admission routes1
Has abstractyes

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