Understanding antagonism: a comment on Sheehan and Bergman
Bibliographic record
Abstract
Sheehan and Bergman (2016) point to Rohwer’s (1982) classic paper as the source of their central insight regarding antagonistic evolution stating that “to our knowledge, he was the first to propose that social recognition may limit the evolution of a quality signal by eliminating the need for a signal in certain social systems.” Although this may not have been the authors’ intent, this phrasing generates the impression that badges of status are some kind of “default setting” and the possibility for social recognition thus “prevents” such signals from evolving, whereas, as originally formulated, and as Sheehan and Bergman (2016) themselves report, the argument is that, when group size is small and social recognition sufficient, badges of status are simply not advantageous. When put this way, it all seems much less antagonistic. To be fair, the authors state explicitly that limitation occurs through the “elimination of need” but, again, this phrasing suggests the presence of something that was subsequently removed. Rohwer’s (1982) argument can equally well be interpreted to mean simply a complete absence of need, and not its elimination. This is a small and trivial point, but the phrasing does help generate the impression that antagonism is central and important, but perhaps this needs more elaboration for why this should be the case.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".