Look me in the eye: A comparison of fine-grained sensitivity to eye contact between 8-year-olds and adults
Bibliographic record
Abstract
Adults perceive that a face is making eye contact with them when the actual fixation position is within a range of 2–4.5° to either side of the bridge of their nose (the cone of gaze) (Gamer & Hecht, 2007). Children as old as 11 years are less accurate than adults at judging whether someone is looking at their eyes or at another part of their face (Lord, 1974). Here, we developed a child-friendly procedure to compare the width and centering of the cone of gaze between 8-year-olds and adults (n = 18/group). Participants sat in front of a computer monitor on which they saw faces fixating the center of the camera lens and a series of surrounding positions (separated by 1.6°) to the left/right (horizontal blocks) or upward/downward (vertical blocks). Participants performed a 3AFC task in which they judged whether the model's gaze on each trial was direct, averted left (or up in vertical blocks), or averted right (or down). For each participant and block type, we fit a psychometric function to the proportion of each response type and calculated the width of the cone of gaze from the crossover points between the fitted “direct” function and the two other functions. The cone was wider in 8-year-olds (M = 7.19°) than adults (M = 6.23°), p < .02, and wider for the vertical (M = 7.62°) than the horizontal (M = 5.80°) axis, p < .001. In both age groups, the cones were centered around exactly direct gaze, whether the centering of each cone was measured from the maximum of the fitted “direct” function or the midpoint between the edges of the cone, with no difference between ages or directions, ps > .05. The results indicate for the first time that 8-year-olds are almost as good as adults in detecting deviations from direct gaze.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".