Bibliographic record
Abstract
Cheating is common in cooperative interactions, but its occurrence can be controlled by various means ranging from rewarding cooperators to active punishment of cheaters. Punishment occurs in the mutualism involving the cleanerfish Labroides dimidiatus and its reef fish clients. When L. dimidiatus cheats, by taking scales and mucus rather than ectoparasites, wronged clients either chase or withhold further visits to the dishonest cleaner, which leads to more cooperative future interactions. Punishment of cheating L. dimidiatus may be effective largely because these cleaners are strictly site-attached, increasing the potential for repeated interactions between individual cleaners and clients. Here, we contrast the patterns of cheating and punishment in L. dimidiatus with its close relative, the less site-attached Labroides bicolor. Overall, L. bicolor had larger home ranges, cheated more often and, contrary to our prediction, were punished by cheated clients as frequently as, and not less often than, L. dimidiatus. However, adult L. bicolor, which had the largest home ranges, did not cheat more than younger conspecifics, suggesting that roaming, and hence the frequency of repeated interactions, has little influence on cheating and retaliation in cleaner-client relationships. We suggest that roaming cleaners offer the only option available to many site-attached reef fish seeking a cleaning service. This asymmetry in scope for partner choice encourages dishonesty by the partner with more options (i.e. L. bicolor), but to be cleaned by a cleaner that sometimes cheats may be a better option than not to be cleaned at all.
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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 | 0.002 | 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 | 0.001 | 0.002 |
| 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".