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Record W2768694727 · doi:10.5539/ies.v10n12p70

Does Skepticism Predict News Media Literacy: A Study on Turkish Young Adults

2017· article· en· W2768694727 on OpenAlexvenueno aff
Osman Yılmaz Kartal, Akan Deniz Yazgan, Remzi Y. Kıncal

Bibliographic record

VenueInternational Education Studies · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicLiteracy, Media, and Education
Canadian institutionsnot available
Fundersnot available
KeywordsSkepticismMedia literacyPsychologyLiteracyMass mediaNews mediaInterpersonal communicationInformation literacyTurkishScientific literacyInformation AgeSocial psychologySociologyMedia studiesPolitical scienceMathematics educationPedagogy

Abstract

fetched live from OpenAlex

The 2010’s are when information and informatics age coexist, information overload has been transformed into a mass engineering tool, “imposing bombardment” has become the norm. The most influential tool of this cultural-industrial act is news media. Efforts to educate young adults, who are most active in touch with information, in view of news media are needed. Skepticism has the potential to improve news media literacy of young adults. The present study investigates whether young adults’ skepticism levels predict young adults’ news media literacy levels. The research problem was analyzed with correlational research model. Two different research populations (Canakkale Onsekiz Mart University and Ataturk University) were determined for the purpose of the study. The results revealed positive, moderate, significant relationships between skepticism levels and news media literacy of young adults. “Self-determining” and “interpersonal understanding” competences - the components of skepticism - have a positive effect on news media literacy. The “search for knowledge” and “questioning mind” has the potential to positively affect news media literacy.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.238
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.055
GPT teacher head0.368
Teacher spread0.313 · 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

Citations5
Published2017
Admission routes1
Has abstractyes

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