Perceptions of Child Facial Cues as a Function of Child Age
Bibliographic record
Abstract
Child facial cues are known to influence adults' perceptions, attributions, and parental care behaviors. But how does the influence of these cues change with age? There are three competing theories regarding the influence of age on child facial cues: younger cues have the strongest influence, older cues have the strongest influence, and age cues do not influence adults. There are empirical findings that provide support for each of these hypotheses. Because previous studies have not focused on measures of adults' desire to provide parental care and have used limited stimulus sets and/or statistics, we conducted two studies to determine how age-related changes in child faces influenced adults' perceptions and ratings in the Hypothetical Adoption Paradigm. We presented approximately 200 adults with images of 12 different children at eight different ages (from six months to six years). Adults' ratings of adoption preference and cuteness were strongly and negatively related to the age of the child facial stimuli, while there was no consistent relationship between child age and adults' ratings of health. Our results support the hypothesis that facial cues associated with younger ages are most effective at eliciting adult responses associated with parental care.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| 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) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".