Bibliographic record
Abstract
While there is an extensive literature on how economic agents bargain to divide an asset, little is known about the decision to initiate bargaining and how the initiation affects the outcome of bargaining. We address these questions in the context of high-stakes poker tournaments in which the last few players often negotiate the division of the remaining prize money rather than risk playing the tournament to the end. In 63% of the tournaments in our sample players enter into negotiations, and in 31%, they successfully reach an agreement. We find that the identity of the player who initiates bargaining affects whether a deal is completed but does not affect the terms of the eventual deal. The initiator tends to have a weaker than average position at the table, but the likelihood that a deal will be completed increases in the initiator's strength in the game and history of winning past tournaments. These findings indicate that initiating negotiations conveys information that is relevant to whether a deal will emerge. Nevertheless, initiating bargaining does not affect the initiator's pay-off in a completed deal. Lastly, we find strong evidence that bargaining tends to be initiated and is more likely to be successful when participants' stakes are about equal, consistent with the theoretical work of Cramton, Gibbons and Klemperer (1987, “Dissolving a Partnership Efficiently”, Econometrica, 55, 615–632).
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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 | 0.001 |
| 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 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".