MétaCan
Menu
Back to cohort
Record W2800080791 · doi:10.1075/itl.00012.rod

The images in television programs and the potential for learning unknown words

2018· article· en· W2800080791 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueITL Review of Applied Linguistics · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicSubtitles and Audiovisual Media
Canadian institutionsCarleton University
Fundersnot available
KeywordsVocabularyPresentation (obstetrics)NarrativeWord (group theory)PsychologyVocabulary learningComputer scienceMultimediaLinguistics

Abstract

fetched live from OpenAlex

Abstract Previous studies have indicated the potential for incidental vocabulary learning through viewing television. The assumption has been that the imagery in television helps learners acquire vocabulary because when they hear an unfamiliar word, the on-screen images provide semantic support. However, the extent to which imagery in authentic television supports learners in this way is unclear. This study examines 90 target words occurring in single seasons of television, and the degree to which their aural occurrence matched the presentation of a potentially supporting image. Results indicate differences in the way imagery supports potential vocabulary learning in documentary television compared with narrative television, and that this supporting imagery occurred concurrently with the aural form more often in documentary television. Research and pedagogical implications are discussed in detail.

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.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.989
Threshold uncertainty score0.253

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.018
GPT teacher head0.278
Teacher spread0.260 · 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