The Role of Simmelian Friendship Ties on Retaliation within Triads
Why this work is in the frame
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Bibliographic record
Abstract
We examine the effect of friendship in triads on retaliatory responses to unfair outcomes that originate from a group member. Drawing on Simmel’s classic discussion of relationships in social triads versus dyads, we hypothesized that the effect of unfairness on retaliation between friends is stronger when the third party in the triad is a mutual friend, rather than a stranger. We also draw on social categorization theory to hypothesize that the effect of unfairness on retaliation between strangers is stronger when the third party is a friend of that stranger than when the triad consists of all strangers. Hypotheses were tested in an experiment where participants negotiated with one another in a three-person exchange network. The results supported our hypothesis that between friends, the increase in retaliation was stronger following an unfair deal when third parties were mutual friends, rather than strangers.
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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 | 0.012 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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 it