The Effects of Control Systems on Cooperation under Environmental Risk
Why this work is in the frame
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Bibliographic record
Abstract
Prior research shows that formal controls such as explicit financial incentives and feedback about partner behavior (or equivalent mutual monitoring) help overcome relational risk in collaborative settings and increase cooperation. Environmental risk requires collaborators to infer cooperation from noisy outcomes, making attributions to their partner’s trustworthiness more difficult and cooperation harder to sustain. We investigate whether prior results on the effectiveness of (removed) formal controls hold under environmental risk. Importantly, we distinguish two common job designs (i.e., whether collaborators can mutually monitor cooperative actions or not) and isolate the effect of this variable from the effect of financial incentives. First, as a baseline with prior studies, we predict and find that mutual monitoring provides reliable information about partner behavior that mitigates difficulties for cooperation introduced by environmental risk. Second, financial incentives continue to have benefits for long-term cooperation (i.e., after their removal) not only when mutual monitoring is present, but also when mutual monitoring is absent and the difficulties for cooperation associated with environmental risk can take full effect. We provide supplemental evidence on the role of trust and perceived relational risk. Our results have implications for organizations’ control system design given environmental risk is inherent in business.
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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 | 0.002 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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