How Moving Together Binds Us Together: The Social Consequences of Interpersonal Entrainment and Group Processes
Bibliographic record
Abstract
Abstract Interpersonal entrainment has been shown to have a wide variety of social consequences which span far beyond those that could be considered purely pro-social. This work reviews all of the social effects of entrainment and the various explanations for them. The group formation framework emerges as a parsimonious account claiming that as we entrain our sense of self is temporarily diluted as an interdependent identity becomes more salient, thus leading to a range of social and psychological consequences which are pro-group. The sense of belonging arising from moving together is conducive towards pro-social behaviours; yet, it also makes the individual more susceptible to adopting the ideology of the group without critical thinking. We argue that the wide landscape of interpersonal entrainment’s effects reflects its primary effect, de-individuation, and the formation of a common group identity amongst co-actors.
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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 | 0.001 | 0.000 |
| 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".