Bibliographic record
Abstract
The present study investigated the role of differential experience in one’s processing of facial age information. Study 1 examined how differential experience with own- and other-race individuals, as well as differential experience with own- and other-age individuals, influences children’s and adults’ abilities to process facial age information. Study 2 examined how differential sociocultural experiences influence adults’ abilities to process facial age information. The results suggest that the influence of differential experience with own- and other-race faces is most evident when individuals have extremely limited to no experience with other-race faces. There was also a clear other-age effect in young adults’ facial age judgments, presumably due to their extensive experience with own-age peers. However 9- to 10-year-olds and 13- to 14-year-olds also showed an advantage in processing facial age information for young adult faces relative to child and middle-age adult faces. Thus, the 9- to 10-year-olds and 13- to 14-year-olds may have also had the most extensive experience with young adult individuals relative to individuals from other age groups. In addition, results suggest that the efficiency with which individuals process facial age information is influenced by differential sociocultural emphases on the need to differentiate between the facial ages of social partners.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".