Quantifying Child-Appeal: The Development and Mixed-Methods Validation of a Methodology for Evaluating Child-Appealing Marketing on Product Packaging
Why this work is in the frame
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Bibliographic record
Abstract
There is no standardized or validated definition or measure of “child-appeal” used in food and beverage marketing policy or research, which can result in heterogeneous outcomes. Therefore, this pilot study aimed to develop and validate the child-appealing packaging (CAP) coding tool, which measures the presence, type, and power of child-appealing marketing on food packaging based on the marketing techniques displayed. Children (n = 15) participated in a mixed-methods validation study comprising a binary classification (child-appealing packaging? Yes/No) and ranking (order of preference/marketing power) activity using mock breakfast cereal packages (quantitative) and focus group discussions (qualitative). The percent agreement, Cohen’s Kappa statistic, Spearman’s Rank correlation, and cross-classification analyses tested the agreement between children’s and the CAP tool’s evaluation of packages’ child-appeal and marketing power (criterion validity) and the content analysis tested the relevance of the CAP marketing techniques (content validity). There was an 80% agreement, and “moderate” pairwise agreement (κ [95% CI]: 0.54 [0.35, 0.73]) between children/CAP binary classifications and “strong” correlation (rs [95% CI]: 0.78 [0.63, 0.89]) between children/CAP rankings of packages, with 71.1% of packages ranked in the exact agreement. The marketing techniques included in the CAP tool corresponded to those children found pertinent. Pilot results suggest the criterion/content validity of the CAP tool for measuring child-appealing marketing on packaging in accordance with children’s preferences.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it