Facing Dominance: Anthropomorphism and the Effect of Product Face Ratio on Consumer Preference
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.
Bibliographic record
Abstract
Abstract A product’s front face (e.g., a watch face or car front) is typically the first point of contact and a key determinant of a consumer’s initial impression about the product. Drawing on evolutionary accounts of human face perception suggesting that the face width-to-height ratio (fWHR: bizygomatic width divided by upper-face height) can signal dominance and affect its overall evaluation, this research is based on the premise that product faces are perceived in much the same way as human faces. Five experiments tested this premise. Results suggest that like human faces, product faces with high (vs. low) fWHR are perceived as more dominant. However, while human faces with high fWHR are liked less, product faces with high fWHR are liked more as revealed by consumer preference and willingness-to-pay scores. The greater preference for the high fWHR product faces is motivated by the consumers’ desire to enhance and signal their own dominant status as evidenced by the moderating effects of type of goal and of usage context. Brand managers and product designers may be particularly interested in these findings since a simple design feature can have potentially significant marketplace impact, as was also confirmed by the field data obtained from secondary sources.
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 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 | 0.005 | 0.001 |
| 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 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it