The Goldilocks contract: The synergistic benefits of combining structure and autonomy for persistence, creativity, and cooperation.
Bibliographic record
Abstract
Contracts are commonly used to regulate a wide range of interactions and relationships. Yet relying on contracts as a mechanism of control often comes at a cost to motivation. Integrating theoretical perspectives from psychology, economics, and organizational theory, we explore this control-motivation dilemma inherent in contracts and present the Contract-Autonomy-Motivation-Performance-Structure (CAMPS) model, which highlights the synergistic benefits of combining structure and autonomy. The model proposes that subtle reductions in the specificity of a contract's language can boost autonomy, which increases intrinsic motivation and improves a range of desirable behaviors. Nine field and laboratory experiments found that less specific contracts increased task persistence, creativity, and cooperation, both immediately and longitudinally, because they boosted autonomy and intrinsic motivation. These positive effects, however, only occurred when contracts provided sufficient structure. Furthermore, the effects were limited to control-oriented clauses (i.e., legal clauses), and did not extend to coordination-oriented clauses (i.e., technical clauses). That is, there were synergistic benefits when a contract served as a scaffold that combined structure with general clauses. Overall, the current model and experiments identify a low-cost solution to the common problem of regulating social relationships: finding the right amount of contract specificity promotes desirable outcomes, including behaviors that are notoriously difficult to contract. The CAMPS model and the current set of empirical findings explain why, when, and how contracts can be used as an effective motivational tool. (PsycINFO Database Record
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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 | 0.003 | 0.002 |
| 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".