A Laboratory Investigation of Verification and Reputation Formation in a Repeated Joint Investment Setting*
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract This paper describes an experiment in which subjects, acting as division managers, exchanged privately held information before making intrafirm investment decisions. Social efficiency required that managers honestly disclose their private information, but managers had individual incentives to send biased messages. These features of the model created an important role for ex post verification, the main manipulation in the experiment. The matching protocol was also manipulated, using both random and continuous matching of subjects. This second manipulation was intended to examine whether an important institutional attribute — the frequency of interaction — would affect the usefulness of verification. The results of the experiment indicate that verification significantly increased the relative frequency of honest messages and the level of social efficiency. However, the improvements from verification were greater in settings where subjects did not interact repeatedly. The data also indicate that, in the continuous matching treatments, responses depended on the history of behavior of the message sender. However, this behavior was not observed in the random matching treatments. Thus, both the efficacy of verification and the extent of reputation formation depended on the institutional setting.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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