Aging Faces and Aging Perceivers: Young and Older Adults are Less Sensitive to Deviations from Normality in Older Than in Young Adult Faces
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
Past studies examining the other-age effect, the phenomenon in which own-age faces are recognized more accurately than other-age faces, are limited in number and report inconsistent results. Here we examine whether the perceptual system is preferentially tuned to differences among young adult faces. In experiment 1 young (18-25 years) and older adult (63-87 years) participants were shown young and older face pairs in which one member of each pair was undistorted and the other had compressed or expanded features. Participants indicated which member of each pair was more normal and which was more expanded. Both age groups were more accurate when tested with young compared with older faces-but only when judging normality. In experiment 2 we tested a separate group of young adults on the same two tasks but with upright and inverted face pairs to examine the differential pattern of results between the normality and discrimination tasks. Inversion impaired performance on the normality task but not the discrimination task and eliminated the young adult advantage in the normality task. Collectively, these results suggest that the face processing system is optimized for young adult faces and that abundant experience with older faces later in life does not reverse this perceptual tuning.
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 | 0.000 | 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 | 0.001 |
| 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