Development of sensitivity to facial expression of pain
Bibliographic record
Abstract
The ability to perceive pain in others is an important human capacity. Its development has not been studied. The present study examined the development of sensitivity to evidence of pain from childhood to early adulthood. One hundred and thirty-four males and females from four age groups (5-6, 8-9, 11-12 years and young adult) took part. They judged the amount of pain displayed on videotaped excerpts of the facial expressions of pain patients. Excerpts were selected to display no pain, some pain and strong pain, based on facial measurements, and were displayed to participants in a signal-detection paradigm. All participant groups were more sensitive to evidence of strong than some pain. The ability to detect pain expressions increased across the young, middle and older groups of children, but older children did not differ from adults. Increasing age was generally associated with increasing sensitivity to more subtle facial signs of pain. The results indicate that the ability to perceive pain in others is already significantly developed by the ages of five to six, but refinements in the ability continue through to early adulthood. These findings represent the first description of the development of the ability to perceive pain in others. Important areas for future research into the neurobiological, personal and social determinants of this ability are highlighted.
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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 | 0.000 | 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".