The Impact of Video-Mediated Communication on Social Predictions and Theory of Mind Activation
Bibliographic record
Abstract
Humans have an ability to predict strangers’ cooperative behavior, an evolutionary trait fostering social cooperation by reducing free riding. This ability is linked to Theory of Mind (ToM), a cognitive mechanism enabling the inference of intentions and behaviours. With the growing use of video-mediated tools like Zoom, it is unclear whether this ability—evolved in face-to-face (FtF) settings—remains intact during video interactions. This study examines how video mediation affects ToM activation; specifically whether video impairs cooperativeness predictions compared to FtF, and whether egocentric biases arise in mediated settings. We propose three hypotheses: prediction is more accurate than chance in FtF, no better than chance in video, and highly egocentric in video. Three studies (n1 = 98, n2 = 120, n3 = 91), confirmed these hypotheses, with post hoc analyses ruling out language, non-verbal cues, and interaction time. A fourth study (n4 = 83) highlighted eye gaze as a factor in prediction accuracy.
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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 | 0.030 |
| 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 | 0.001 | 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".