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Record W2066085782 · doi:10.1080/18377122.2014.940812

Online, tuned in, turned on: multimedia approaches to fostering critical media health literacy for adolescents

2014· article· en· W2066085782 on OpenAlexafffund
Deborah L. Begoray, Elizabeth Banister, Joan Higgins, Robin Wilmot

Bibliographic record

VenueAsia-Pacific Journal of Health Sport and Physical Education · 2014
Typearticle
Languageen
FieldHealth Professions
TopicHealth Literacy and Information Accessibility
Canadian institutionsUniversity of Victoria
FundersCanada Research Chairs
KeywordsMedia literacyCritical literacyHealth literacySociocultural evolutionHealth communicationInformation literacyCritical thinkingLiteracyHealth educationHealth informationMultimediaPsychologyPedagogyMathematics educationSociologyPublic relationsComputer scienceMedicinePolitical sciencePublic healthHealth careNursing

Abstract

fetched live from OpenAlex

The commercial media is an influential sociocultural force and transmitter of health information especially for adolescents. Instruction in critical media health literacy, a combination of concepts from critical health literacy and critical media literacy, is a potentially effective means of raising adolescents’ awareness about commercial media and its influence on their health. We first provide background on critical media health literacy for adolescents. We then discuss the potential for involving adolescents in creating multimedia to demonstrate basic principles of critical media health literacy skills. Using excerpts from two of our research projects to illustrate our ideas, we draw conclusions and suggest future research in critical media health literacy for adolescents.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.134
GPT teacher head0.468
Teacher spread0.334 · 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

Citations10
Published2014
Admission routes2
Has abstractyes

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