An Experimental Study of Credible Deviations and ACDC
Bibliographic record
Abstract
We test the Average Credible Deviation Criterion (ACDC), a stability measure and refinement for cheap talk equilibria introduced in De Groot Ruiz, Offerman & Onderstal (2011b). ACDC has been shown to be predictive under general conditions and to organize data well in previous experiments meant to test other concepts. This experiment provides the first systematic test of whether and to which degree credible deviations matter for the stability of cheap talk equilibria. Furthermore, it tests ACDC in a new setting. We also introduce a neologism dynamic to explain the main dynamic characteristics of our data. Our main result is that credible deviations matter and matter gradually, as predicted by ACDC. In addition, our data support the predictions of ACDC in settings where existing concepts are silent. Finally, we test the prediction derived in De Groot Ruiz, Offerman & Onderstal (2011a) about bargaining power and information transmission. We find that, as predicted, less information is transmitted as the Sender's relative power decreases.
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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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".