On the incentive effects of monitoring: evidence from the lab and the field
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 Several experimental studies have shown that the crowding-out effect of monitoring may outweigh its disciplining effect through intrinsic motivation destruction, thereby reducing effort. However, most of these experiments use numeric effort tasks that subjects may not be intrinsically motivated to complete. This paper aims to analyze the incentive effects of monitoring using a real-effort task for which intrinsic motivation is more likely to exist. We conducted two similar experiments, in the lab in Montreal and in the field in Ouagadougou. In contrast to the lab, subjects in the field are unaware they are taking part in an experiment. The following results are observed both in the lab and in the field. Relative to the baseline treatment, we find that our two monitoring treatments significantly increase effort, in line with agency theory. However, effort levels are not significantly different between the monitoring treatments. Finally, increasing the subjects’ wage is found to have no effect on effort.
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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 | 0.000 | 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 | 0.001 | 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 it