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Record W2033455217 · doi:10.1080/10454446.2013.724370

Measuring the Impact of Product Placement on Children Using Digital Brand Integration

2013· article· en· W2033455217 on OpenAlex
Simon Hudson, Charlene Elliott

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

VenueJournal of Food Products Marketing · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Marketing and Social Media
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsRecallProduct (mathematics)Product placementMarketingAdvertisingBusinessPsychologyFood productsMathematicsFood science

Abstract

fetched live from OpenAlex

Recent marketing literature has called for more research that focuses on the influence of new media on children and, specifically, the use of product placement. The objective of this study was to analyze the impact of food and beverage product placements on children of different ages. Using an experimental approach, groups of children viewed the same television program, but with either healthy products or unhealthy brands digitally inserted. A detailed survey then measured aided and unaided recall and immediate choice behavior. In total, 225 children from two schools took part in the experiment. The results indicated strong recall for the products placed, especially for the unhealthy products, and particularly among older children. However, the placements had only a modest influence on immediate behavior, with regression analysis suggesting that the packaging was more significant in influencing choice. Theoretical and practical implications are discussed.

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)0.005
metaresearch head score (Gemma)0.017
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.805
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.034
GPT teacher head0.284
Teacher spread0.250 · 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