Children’s preference for eyeglasses colour: towards a quantified hierarchical perception model
Bibliographic record
Abstract
Product perception is a core dimension of ergonomics, encompassing how individuals cognitively and emotionally interpret product attributes. Eyeglasses, as a salient and prevalent facial appearance-related product for children, whose self- and peer-perceptions are both complex and influential. Yet, how these perceptions shape children's preferences remains underexplored. Moreover, colour represents one of the most immediate product attributes, which is associated with gender. Accordingly, this study investigates the mechanisms linking children's emotional perceptions to their eyeglasses colour preferences, both boys and girls. A quantified hierarchical perception model was developed through a psychological experiment with 32 children (17 boys, 15 girls) and subsequent statistical and regression analyses. Using eyeglasses as a representative case, the model offers practical and quantitative guidance for colour design in facial appearance-related products. Overall, the study contributes to advancing knowledge of children's perception and decision-making in the domains of colour, ergonomics, and product design.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".