Productivity-Target Difficulty, Target-Based Pay, and Outside-the-Box Thinking
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 In an environment where individual productivity can be increased through efforts directed at a conventional task approach and more efficient task approaches that can be identified by thinking outside-the-box, we examine the effects of productivity-target difficulty and pay contingent on meeting and beating this target (i.e., target-based pay). We argue that while challenging targets and target-based pay can hinder the discovery of production efficiencies, they can motivate high productive effort whereby individuals work harder and more productively using either the conventional task approach or more efficient task approaches when discovered. Results of a laboratory experiment support our predictions. Individuals assigned an easy productivity target and paid a fixed wage identify a greater number of production efficiencies than those with either challenging targets or target-based pay. However, individuals with challenging targets and/or target-based pay have higher productivity per production efficiency discovered, suggesting these control tools better motivate productive effort. Collectively, our results suggest that the ultimate effectiveness of these control tools will likely hinge on the importance of promoting the discovery of production efficiencies relative to motivating productive effort. In doing so, our results provide a better understanding of conflicting prescriptions from the practitioner literature and business press.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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