Genuine, suppressed and faked facial expressions of pain in children
Bibliographic record
Abstract
Children's efforts to hide or exaggerate facial expressions of pain were compared to their genuine expressions using the cold pressor task. Fifty healthy 8- to 12-year-olds (25 boys, 25 girls) submerged their hands in cold and warm water and were instructed about what to show on their faces. Cold 10 degrees C water was used for the genuine and suppressed conditions and warm 30 degrees C water was used for the faked condition. Facial activity was videotaped and coded using the Facial Action Coding System to provide objective, detailed accounts of facial expressions in each condition, as well as during a baseline condition. Parents were subsequently asked to correctly identify each of the four conditions by viewing each video clip twice. Faked expressions of pain in children were found to show more frequent and more intense facial actions compared to their genuine pain expression, indicating that children had some understanding but were not fully successful in faking expressions of pain. Children's suppressed expressions, however, showed no differences from baseline facial actions, indicating that they were able to successfully suppress their expressions of pain. Parents correctly identified the four conditions significantly more frequently than would be expected by chance. They were generally quite successful at detecting faked pain, but experienced difficulty differentiating among the other conditions. The results indicate that children are capable of controlling their facial expressions of pain when instructed to do so, but are better able to hide their pain than to fake it.
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How this classification was reachedexpand
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 | 0.003 | 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 | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".